---
tags:
- espnet
- audio
- automatic-speech-recognition
language: zh
datasets:
- wenetspeech
license: cc-by-4.0
---

## ESPnet2 ASR model

### `espnet/pengcheng_guo_wenetspeech_asr_train_asr_raw_zh_char`

This model was trained by Pengcheng Guo using wenetspeech recipe in [espnet](https://github.com/espnet/espnet/).

### Demo: How to use in ESPnet2

```bash
cd espnet
git checkout 5c21f63e45e0961a5d817017c282b0cafd68a3aa
pip install -e .
cd egs2/wenetspeech/asr1
./run.sh --skip_data_prep false --skip_train true --download_model espnet/pengcheng_guo_wenetspeech_asr_train_asr_raw_zh_char
```

<!-- Generated by scripts/utils/show_asr_result.sh -->
# RESULTS
## Environments
- date: `Wed Oct  6 15:11:20 CST 2021`
- python version: `3.8.11 (default, Aug  3 2021, 15:09:35)  [GCC 7.5.0]`
- espnet version: `espnet 0.10.2a1`
- pytorch version: `pytorch 1.9.0`
- Git hash: ``
  - Commit date: ``

## asr_train_asr_conformer_raw_zh_char
### WER

|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
|---|---|---|---|---|---|---|---|---|
|decode_asr_rnn_asr_model_valid.acc.ave_10best/aishell_test|7176|7176|67.1|32.9|0.0|0.1|33.0|32.9|
|decode_asr_rnn_asr_model_valid.acc.ave_10best/dev|13825|16684|32.1|54.1|13.8|0.1|68.0|64.2|
|decode_asr_rnn_asr_model_valid.acc.ave_10best/test_meeting|8370|8599|13.4|84.6|2.0|0.1|86.7|86.8|
|decode_asr_rnn_asr_model_valid.acc.ave_10best/test_net|24774|25995|46.2|50.4|3.4|1.1|54.9|52.5|

### CER

|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
|---|---|---|---|---|---|---|---|---|
|decode_asr_rnn_asr_model_valid.acc.ave_10best/aishell_test|7176|104765|96.3|3.6|0.1|0.2|3.9|32.9|
|decode_asr_rnn_asr_model_valid.acc.ave_10bestdev|13825|333357|90.7|3.4|5.9|0.4|9.7|64.2|
|decode_asr_rnn_asr_model_valid.acc.ave_10best/test_meeting|8370|220614|84.6|5.0|10.4|0.5|15.9|86.8|
|decode_asr_rnn_asr_model_valid.acc.ave_10best/test_net|24774|416968|91.8|5.3|2.9|0.6|8.8|52.5|

### TER

|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
|---|---|---|---|---|---|---|---|---|

## ASR config

<details><summary>expand</summary>

```
config: conf/train_asr_conformer.yaml
print_config: false
log_level: INFO
dry_run: false
iterator_type: sequence
output_dir: exp/asr_train_asr_conformer_raw_zh_char
ngpu: 1
seed: 0
num_workers: 1
num_att_plot: 3
dist_backend: nccl
dist_init_method: env://
dist_world_size: 8
dist_rank: 0
local_rank: 0
dist_master_addr: localhost
dist_master_port: 44205
dist_launcher: null
multiprocessing_distributed: true
unused_parameters: false
sharded_ddp: false
cudnn_enabled: true
cudnn_benchmark: false
cudnn_deterministic: true
collect_stats: false
write_collected_feats: false
max_epoch: 30
patience: null
val_scheduler_criterion:
- valid
- acc
early_stopping_criterion:
- valid
- loss
- min
best_model_criterion:
-   - valid
    - acc
    - max
keep_nbest_models: 10
grad_clip: 5
grad_clip_type: 2.0
grad_noise: false
accum_grad: 4
no_forward_run: false
resume: true
train_dtype: float32
use_amp: false
log_interval: null
use_tensorboard: true
use_wandb: false
wandb_project: null
wandb_id: null
wandb_entity: null
wandb_name: null
wandb_model_log_interval: -1
detect_anomaly: false
pretrain_path: null
init_param: []
ignore_init_mismatch: false
freeze_param: []
num_iters_per_epoch: null
batch_size: 20
valid_batch_size: null
batch_bins: 30000000
valid_batch_bins: null
train_shape_file:
- exp/asr_stats_raw_zh_char/train/speech_shape
- exp/asr_stats_raw_zh_char/train/text_shape.char
valid_shape_file:
- exp/asr_stats_raw_zh_char/valid/speech_shape
- exp/asr_stats_raw_zh_char/valid/text_shape.char
batch_type: numel
valid_batch_type: null
fold_length:
- 51200
- 150
sort_in_batch: descending
sort_batch: descending
multiple_iterator: false
chunk_length: 500
chunk_shift_ratio: 0.5
num_cache_chunks: 1024
train_data_path_and_name_and_type:
-   - dump/raw/train_l/wav.scp
    - speech
    - sound
-   - dump/raw/train_l/text
    - text
    - text
valid_data_path_and_name_and_type:
-   - dump/raw/dev/wav.scp
    - speech
    - sound
-   - dump/raw/dev/text
    - text
    - text
allow_variable_data_keys: false
max_cache_size: 0.0
max_cache_fd: 32
valid_max_cache_size: null
optim: adam
optim_conf:
    lr: 0.0015
scheduler: warmuplr
scheduler_conf:
    warmup_steps: 30000
token_list:
- <blank>
- <unk>
- 的
- 我
- 是
- 你
- 了
- 一
- 不
- 这
- 个
- 有
- 就
- 们
- 在
- 他
- 人
- 么
- 来
- 说
- 那
- 要
- 好
- 啊
- 大
- 到
- 上
- 也
- 没
- 都
- 去
- 能
- 子
- 会
- 为
- 得
- 时
- 还
- 可
- 以
- 什
- 家
- 后
- 看
- 呢
- 对
- 事
- 天
- 下
- 过
- 想
- 多
- 小
- 出
- 自
- 儿
- 生
- 给
- 里
- 现
- 着
- 然
- 吧
- 样
- 道
- 吗
- 心
- 跟
- 中
- 很
- 点
- 年
- 和
- 地
- 怎
- 知
- 十
- 老
- 当
- 把
- 话
- 别
- 所
- 之
- 情
- 实
- 开
- 面
- 回
- 行
- 国
- 做
- 己
- 经
- 如
- 真
- 起
- 候
- 些
- 让
- 发
- 她
- 觉
- 但
- 成
- 定
- 意
- 二
- 长
- 最
- 方
- 三
- 前
- 因
- 用
- 呀
- 种
- 只
- 走
- 其
- 问
- 再
- 果
- 而
- 分
- 两
- 打
- 学
- 间
- 您
- 本
- 于
- 明
- 手
- 公
- 听
- 比
- 作
- 女
- 太
- 今
- 从
- 关
- 妈
- 同
- 法
- 动
- 已
- 见
- 才
- 孩
- 感
- 吃
- 常
- 次
- 它
- 进
- 先
- 找
- 身
- 全
- 理
- 又
- 力
- 正
- 主
- 应
- 高
- 被
- 钱
- 快
- 等
- 头
- 重
- 车
- 谢
- 日
- 东
- 放
- 无
- 工
- 咱
- 哪
- 五
- 者
- 像
- 西
- 该
- 干
- 相
- 信
- 机
- 百
- 特
- 业
- 活
- 师
- 边
- 爱
- 友
- 新
- 外
- 位
- 更
- 直
- 几
- 第
- 非
- 四
- 题
- 接
- 少
- 哥
- 死
- 完
- 刚
- 电
- 气
- 安
- 爸
- 白
- 告
- 美
- 解
- 叫
- 月
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- 欢
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- 体
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- 部
- 场
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- 结
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- 总
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- 通
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- 王
- 思
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- 名
- 平
- 系
- 文
- 帮
- 路
- 变
- 记
- 水
- 九
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- 男
- 度
- 报
- 六
- 张
- 管
- 够
- 性
- 表
- 提
- 何
- 讲
- 期
- 拿
- 保
- 嘛
- 司
- 原
- 始
- 此
- 诉
- 处
- 清
- 内
- 产
- 金
- 晚
- 早
- 交
- 离
- 眼
- 队
- 七
- 入
- 山
- 代
- 市
- 海
- 物
- 零
- 望
- 世
- 婚
- 命
- 越
- 收
- 向
- 花
- 房
- 错
- 节
- 父
- 反
- 战
- 买
- 量
- 或
- 员
- 号
- 千
- 怕
- 底
- 且
- 品
- 民
- 化
- 爷
- 并
- 与
- 服
- 需
- 资
- 求
- 教
- 娘
- 医
- 数
- 院
- 书
- 利
- 往
- 确
- 各
- 单
- 风
- 送
- 必
- 条
- 包
- 准
- 光
- 整
- 病
- 弟
- 嗯
- 计
- 照
- 强
- 务
- 影
- 城
- 夫
- 俩
- 决
- 声
- 连
- 乐
- 息
- 远
- 北
- 至
- 饭
- 留
- 宝
- 神
- 近
- 考
- 备
- 案
- 界
- 容
- 况
- 母
- 较
- 持
- 证
- 选
- 制
- 程
- 喝
- 害
- 字
- 失
- 立
- 台
- 玩
- 查
- 块
- 便
- 挺
- 段
- 周
- 由
- 句
- 紧
- 李
- 据
- 杀
- 南
- 商
- 识
- 网
- 式
- 愿
- 传
- 流
- 消
- 伤
- 根
- 演
- 希
- 故
- 坐
- 建
- 注
- 许
- 调
- 共
- 空
- 半
- 却
- 酒
- 联
- 微
- 言
- 肯
- 赶
- 跑
- 笑
- 区
- 岁
- 红
- 达
- 官
- 轻
- 易
- 火
- 线
- 拉
- 首
- 导
- 团
- 慢
- 指
- 写
- 深
- 论
- 片
- 改
- 啥
- 满
- 步
- 音
- 功
- 聊
- 客
- 未
- 格
- 基
- 睡
- 观
- 份
- 视
- 色
- 价
- 政
- 转
- 终
- 复
- 啦
- 呃
- 阿
- 倒
- 义
- 警
- 林
- 使
- 科
- 运
- 苦
- 待
- 费
- 随
- 救
- 试
- 班
- 敢
- 精
- 及
- 术
- 造
- 续
- 养
- 展
- 答
- 绝
- 众
- 站
- 妹
- 差
- 谈
- 卖
- 播
- 创
- 领
- 象
- 志
- 投
- 习
- 兄
- 元
- 皇
- 专
- 态
- 急
- 局
- 兴
- 楚
- 飞
- 护
- 装
- 热
- 奶
- 取
- 设
- 游
- 读
- 福
- 药
- 担
- 历
- 忙
- 规
- 掉
- 刘
- 切
- 断
- 尽
- 社
- 久
- 支
- 板
- 星
- 姑
- 曾
- 突
- 除
- 华
- 责
- 排
- 京
- 值
- 士
- 统
- 换
- 德
- 衣
- 组
- 示
- 脸
- 刻
- 黑
- 遇
- 虽
- 顾
- 戏
- 怪
- 懂
- 叔
- 夜
- 陈
- 亮
- 江
- 兵
- 负
- 布
- 青
- 落
- 推
- 假
- 类
- 令
- 技
- 英
- 质
- 黄
- 治
- 形
- 助
- 球
- 歌
- 参
- 广
- 继
- 简
- 画
- 奇
- 陪
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- 险
- 须
- 念
- 迎
- 幸
- 抓
- 破
- 另
- 争
- 竟
- 户
- 律
- 择
- 究
- 龙
- 足
- 店
- 脑
- 斯
- 党
- 权
- 约
- 疑
- 议
- 严
- 密
- 克
- 存
- 穿
- 承
- 校
- 击
- 际
- 标
- 云
- 营
- 察
- 超
- 食
- 集
- 级
- 礼
- 静
- 背
- 武
- 初
- 拍
- 梦
- 验
- 响
- 角
- 石
- 股
- 追
- 怀
- 婆
- 适
- 独
- 忘
- 血
- 醒
- 具
- 罪
- 享
- 毛
- 香
- 状
- 配
- 靠
- 语
- 仅
- 低
- 细
- 米
- 既
- 钟
- 极
- 停
- 味
- 则
- 油
- 器
- 楼
- 菜
- 研
- 互
- 压
- 贵
- 村
- 属
- 派
- 乎
- 坏
- 控
- 显
- 图
- 双
- 职
- 永
- 哈
- 鬼
- 依
- 料
- 按
- 府
- 坚
- 某
- 甚
- 居
- 练
- 顺
- 模
- 即
- 州
- 引
- 乱
- 速
- 庭
- 朝
- 室
- 似
- 付
- 划
- 尔
- 境
- 犯
- 烦
- 环
- 伙
- 巴
- 春
- 古
- 妇
- 势
- 款
- 增
- 财
- 河
- 守
- 虑
- 汉
- 枪
- 妻
- 爹
- 弄
- 委
- 企
- 冲
- 置
- 麻
- 育
- 项
- 防
- 胡
- 杨
- 致
- 辈
- 括
- 毕
- 卫
- 修
- 史
- 型
- 牌
- 嘴
- 苏
- 群
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- 搞
- 围
- 土
- 毒
- 唱
- 冷
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- 跳
- 脚
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- 剧
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- 借
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- 银
- 优
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- 狗
- 退
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- 否
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- 章
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- 素
- 旅
- 临
- 挑
- 唐
- 露
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- 舞
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- 封
- 逃
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- 疼
- 败
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- 敌
- 散
- 采
- 翻
- 缺
- 胜
- 免
- 销
- 鸡
- 降
- 波
- 测
- 限
- 释
- 忍
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- 床
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- 茶
- 码
- 宁
- 乡
- 辛
- 彩
- 亚
- 浪
- 漂
- 庆
- 训
- 范
- 烧
- 词
- 吵
- 媳
- 探
- 余
- 恐
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- 农
- 遍
- 舒
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- 构
- 呼
- 丝
- 执
- 雅
- 惯
- 右
- 脱
- 恩
- 野
- 折
- 趣
- 笔
- 谓
- 盘
- 贝
- 宣
- 绍
- 嘉
- 宋
- 抢
- 嫌
- 尊
- 碰
- 绪
- 丢
- 厉
- 沙
- 轮
- 施
- 织
- 托
- 县
- 策
- 杯
- 逼
- 傻
- 束
- 街
- 疗
- 益
- 骨
- 迷
- 姻
- 恶
- 默
- 寻
- 搜
- 哦
- 材
- 吸
- 劳
- 勇
- 占
- 暴
- 船
- 徐
- 虎
- 融
- 异
- 审
- 攻
- 雷
- 稳
- 呗
- 输
- 睛
- 臣
- 端
- 威
- 秋
- 欧
- 冰
- 韩
- 减
- <space>
- 操
- 混
- 汽
- 暗
- 隐
- 嫂
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- 喏
- 囹
- 圄
- 砭
- 邕
- 犍
- 鸮
- 剜
- 琚
- 瘢
- 魑
- 眦
- 锉
- 柘
- 痦
- 苕
- 牯
- 湟
- 厝
- 濛
- 赭
- 馐
- 蜇
- 嶂
- 贲
- 靼
- 臬
- 陲
- 潞
- 芩
- 腓
- 锨
- 寮
- 於
- 洇
- 愠
- 疖
- 鹧
- 鸪
- 茕
- 戕
- 壬
- 庾
- 莒
- 鹈
- 鹕
- 蠹
- 勐
- 疥
- 辎
- 耒
- 嗬
- 沔
- 睥
- 邙
- 篾
- 揩
- 肱
- 胍
- 磬
- 菟
- 豢
- 垓
- 唑
- 剌
- 阗
- 汜
- 佤
- 璟
- 麽
- 鬻
- 怏
- 蕤
- 茭
- 睚
- 淙
- 牍
- 榫
- 濯
- 稹
- 媾
- 悱
- 骶
- 蛭
- 鞣
- 椁
- 槊
- 擢
- 滢
- 佚
- 菡
- 沭
- 扦
- 镆
- 闾
- 缛
- 窠
- 疣
- 骠
- 俅
- 喙
- 蹼
- 硼
- 黩
- 腴
- 醮
- 邛
- 漯
- 豉
- 昶
- 刿
- 凇
- 鲅
- 舸
- 邳
- 俟
- 铰
- 翌
- 鳟
- 葳
- 寤
- 碣
- 秭
- 揠
- 熵
- 燧
- 靛
- 嵊
- 窨
- 鹗
- 芎
- 颢
- 佶
- 骢
- 圜
- 岘
- 燊
- 壅
- 畲
- 萘
- 煊
- 粲
- 倌
- 嗳
- 橹
- 椽
- 夔
- 鲑
- 赧
- 殄
- 沆
- 瀣
- 廪
- 舢
- 狍
- 挈
- 鹳
- 蚜
- 彧
- 羟
- 盥
- 镛
- 痈
- 蜊
- 皲
- 篦
- 喑
- 鲢
- 邡
- 蕲
- 僳
- 秣
- 蛉
- 讫
- 祗
- 鹩
- 撷
- 狎
- 郓
- 镕
- 榉
- 鲷
- 娣
- 淝
- 桷
- 镉
- 郫
- 髌
- 醪
- 僭
- 伧
- 嵬
- 苁
- 鹘
- 徭
- 歃
- 阕
- 鸱
- 貉
- 闳
- 坻
- 缙
- 媪
- 莨
- 菪
- 绦
- 恫
- 崆
- 喟
- 葺
- 逶
- 迤
- 骈
- 馔
- 苎
- 溘
- 垭
- 樯
- 诤
- 魃
- 搽
- 绀
- 蚴
- 澶
- 蒺
- 罘
- 眙
- 怍
- 來
- 荪
- 贶
- 亓
- 唻
- 畈
- 谌
- 芨
- 鲀
- 窸
- 窣
- 荜
- 楫
- 衮
- 趵
- 勰
- 髯
- 椴
- 缶
- 荸
- 秫
- 菖
- 甙
- 翦
- 椟
- 峤
- 掼
- 謇
- 洄
- 鄯
- 妗
- 浐
- 颀
- 箸
- 畦
- 痼
- 橛
- 鲛
- 蝾
- 愍
- 蒹
- 嘁
- 韪
- 劭
- 垅
- 暹
- 僮
- 稗
- 筚
- 煅
- 嬅
- 蜉
- 骝
- 碚
- 冼
- 吶
- 洹
- 郧
- 炴
- 绌
- 泠
- 呓
- 簋
- 溴
- 篁
- 仟
- 锟
- 羧
- 鹞
- 嘬
- 渌
- 笸
- 霰
- 稔
- 钡
- 齁
- 胪
- 衾
- 尻
- 洮
- 蘅
- 鲳
- 殂
- 腭
- 涔
- 蝣
- 孳
- 澍
- 钼
- 蒡
- 枳
- 渑
- 茼
- 馕
- 埙
- 珣
- 菘
- 邰
- 樾
- 铱
- 鳐
- 唔
- 篙
- 箜
- 篌
- 耆
- 啫
- 枞
- 杼
- 嵋
- 舂
- 娉
- 铨
- 崃
- 笳
- 邗
- 逡
- 僖
- 泫
- 疴
- 捱
- 醅
- 堇
- 肄
- 荇
- 虬
- 谯
- 酞
- 桡
- 艮
- 膦
- 艹
- 啻
- 滏
- 茆
- 圪
- 磡
- 麼
- 闼
- 郯
- 仡
- 氐
- 贽
- 俦
- 蓖
- 跹
- 帏
- 氅
- 趿
- 暝
- 缟
- 棹
- 滹
- 毖
- 蝰
- 虻
- 缫
- 诮
- 闩
- ○
- 潴
- 樨
- 瘘
- 襦
- 妤
- 郾
- 衿
- 鸷
- 旰
- 镢
- 傈
- 倨
- 笏
- 蒽
- 醌
- 驽
- 浠
- 涠
- 蓁
- 柞
- 钺
- 蜮
- 诂
- 徵
- 锆
- 椋
- 叻
- 廿
- 藁
- 乜
- 摈
- 這
- 茌
- 辊
- 岬
- 郇
- 杓
- 轳
- 酎
- 蟥
- 時
- 镒
- 蚬
- 澹
- 赟
- 後
- 怿
- 箐
- 囍
- 揆
- 蹁
- 鬄
- 苫
- 蕖
- 卺
- 辔
- 偈
- 俳
- 吲
- 哚
- 瘆
- 蕞
- 笞
- 氩
- 嫘
- 墁
- 帔
- 褡
- 裢
- 乩
- 褊
- 颏
- 喒
- 錾
- 皌
- 戗
- 唪
- 啭
- 伥
- 茔
- 斫
- 齉
- 仵
- 赉
- 吡
- 啶
- 蹇
- 螅
- 汊
- 湓
- 凫
- 珙
- 腈
- 洌
- Ω
- 憷
- 跶
- 抔
- 濞
- 崤
- 殍
- 浥
- 铳
- 酽
- 馑
- 髂
- 隗
- 韫
- 晷
- 诒
- 埭
- 鹪
- 蕻
- 昃
- 瓠
- 萁
- 癔
- 怩
- 疳
- 跖
- 疔
- 簟
- 汆
- 疠
- 卟
- 墒
- 穰
- 铍
- 珥
- 钤
- 隻
- 樓
- 墎
- 鳜
- 沒
- 岀
- 杪
- 単
- 鲧
- 呋
- 彀
- 祇
- 豸
- 胴
- 唷
- 丨
- 燚
- 麴
- 觇
- 缑
- 橐
- 蚡
- 朊
- 俣
- 垡
- <sos/eos>
init: null
input_size: null
ctc_conf:
    ignore_nan_grad: true
model_conf:
    ctc_weight: 0.3
    lsm_weight: 0.1
    length_normalized_loss: false
use_preprocessor: true
use_preprocessor_valid: false
token_type: char
bpemodel: null
non_linguistic_symbols: null
cleaner: null
g2p: null
speech_volume_normalize: null
rir_scp: null
rir_utt_prefix: null
rir_apply_prob: 1.0
noise_scp: null
noise_utt_prefix: null
noise_apply_prob: 1.0
noise_db_range: '13_15'
frontend: default
frontend_conf:
    fs: 16k
specaug: specaug
specaug_conf:
    apply_time_warp: true
    time_warp_window: 5
    time_warp_mode: bicubic
    apply_freq_mask: true
    freq_mask_width_range:
    - 0
    - 30
    num_freq_mask: 2
    apply_time_mask: true
    time_mask_width_range:
    - 0
    - 40
    num_time_mask: 2
normalize: global_mvn
normalize_conf:
    stats_file: exp/asr_stats_raw_zh_char/train/feats_stats.npz
preencoder: null
preencoder_conf: {}
encoder: conformer
encoder_conf:
    output_size: 512
    attention_heads: 8
    linear_units: 2048
    num_blocks: 12
    dropout_rate: 0.1
    positional_dropout_rate: 0.1
    attention_dropout_rate: 0.0
    input_layer: conv2d
    normalize_before: true
    rel_pos_type: latest
    pos_enc_layer_type: rel_pos
    selfattention_layer_type: rel_selfattn
    activation_type: swish
    macaron_style: true
    use_cnn_module: true
    cnn_module_kernel: 15
postencoder: null
postencoder_conf: {}
decoder: transformer
decoder_conf:
    attention_heads: 8
    linear_units: 2048
    num_blocks: 6
    dropout_rate: 0.1
    positional_dropout_rate: 0.1
    self_attention_dropout_rate: 0.0
    src_attention_dropout_rate: 0.0
required:
- output_dir
- token_list
version: 0.10.2a1
distributed: true
```

</details>

## LM config

<details><summary>expand</summary>

```
NONE
```

</details>


---
tags:
- espnet
- audio
- text-to-speech
language: ja
datasets:
- jsut
license: cc-by-4.0
---
## ESPnet2 TTS pretrained model
### `kan-bayashi/jsut_tts_train_conformer_fastspeech2_tacotron2_teacher_raw_phn_jaconv_pyopenjtalk_prosody_train.loss.ave`
♻ Imported from https://zenodo.org/record/5499050/

This model was trained by kan-bayashi using jsut/tts1 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
```python
# coming soon
```
### Citing ESPnet
```BibTex
@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}
@inproceedings{hayashi2020espnet,
  title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit},
  author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu},
  booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={7654--7658},
  year={2020},
  organization={IEEE}
}
```
or arXiv:
```bibtex
@misc{watanabe2018espnet,
      title={ESPnet: End-to-End Speech Processing Toolkit},
      author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
      year={2018},
      eprint={1804.00015},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```


---
tags:
- espnet
- audio
- text-to-speech
language: ja
datasets:
- jsut
license: cc-by-4.0
---
## ESPnet2 TTS pretrained model
### `kan-bayashi/jsut_vits_prosody`
♻ Imported from https://zenodo.org/record/5521354/

This model was trained by kan-bayashi using jsut/tts1 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
```python
# coming soon
```
### Citing ESPnet
```BibTex
@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}
@inproceedings{hayashi2020espnet,
  title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit},
  author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu},
  booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={7654--7658},
  year={2020},
  organization={IEEE}
}
```
or arXiv:
```bibtex
@misc{watanabe2018espnet,
      title={ESPnet: End-to-End Speech Processing Toolkit},
      author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
      year={2018},
      eprint={1804.00015},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```


---
tags:
- espnet
- audio
- speech-translation
language: noinfo
datasets:
- iwslt22_dialect
license: cc-by-4.0
---

## ESPnet2 ST model

### `espnet/brianyan918_iwslt22_dialect_train_st_conformer_ctc0.3_lr2e-3_warmup15k_newspecaug`

This model was trained by Brian Yan using iwslt22_dialect recipe in [espnet](https://github.com/espnet/espnet/).

### Demo: How to use in ESPnet2

```bash
cd espnet
git checkout 77fce65312877a132bbae01917ad26b74f6e2e14
pip install -e .
cd egs2/iwslt22_dialect/st1
./run.sh --skip_data_prep false --skip_train true --download_model espnet/brianyan918_iwslt22_dialect_train_st_conformer_ctc0.3_lr2e-3_warmup15k_newspecaug
```

<!-- Generated by scripts/utils/show_st_results.sh -->
# RESULTS
## Environments
- date: `Tue Feb  8 12:54:12 EST 2022`
- python version: `3.8.12 (default, Oct 12 2021, 13:49:34)  [GCC 7.5.0]`
- espnet version: `espnet 0.10.7a1`
- pytorch version: `pytorch 1.8.1`
- Git hash: `77fce65312877a132bbae01917ad26b74f6e2e14`
  - Commit date: `Tue Feb 8 10:48:10 2022 -0500`

## st_train_st_conformer_ctc0.3_lr2e-3_warmup15k_newspecaug_raw_bpe_tc1000_sp
### BLEU

|dataset|bleu_score|verbose_score|
|---|---|---|
pen2_st_model_valid.acc.ave|13.9|44.0/21.8/11.4/6.2 (BP = 0.859 ratio = 0.868 hyp_len = 36614 ref_len = 42181)

## ST config

<details><summary>expand</summary>

```
config: conf/tuning/train_st_conformer_ctc0.3_lr2e-3_warmup15k_newspecaug.yaml
print_config: false
log_level: INFO
dry_run: false
iterator_type: sequence
output_dir: exp/st_train_st_conformer_ctc0.3_lr2e-3_warmup15k_newspecaug_raw_bpe_tc1000_sp
ngpu: 1
seed: 0
num_workers: 1
num_att_plot: 3
dist_backend: nccl
dist_init_method: env://
dist_world_size: null
dist_rank: null
local_rank: 0
dist_master_addr: null
dist_master_port: null
dist_launcher: null
multiprocessing_distributed: false
unused_parameters: false
sharded_ddp: false
cudnn_enabled: true
cudnn_benchmark: false
cudnn_deterministic: true
collect_stats: false
write_collected_feats: false
max_epoch: 80
patience: null
val_scheduler_criterion:
- valid
- loss
early_stopping_criterion:
- valid
- loss
- min
best_model_criterion:
-   - valid
    - acc
    - max
keep_nbest_models: 10
nbest_averaging_interval: 0
grad_clip: 5.0
grad_clip_type: 2.0
grad_noise: false
accum_grad: 2
no_forward_run: false
resume: true
train_dtype: float32
use_amp: false
log_interval: null
use_matplotlib: true
use_tensorboard: true
use_wandb: false
wandb_project: null
wandb_id: null
wandb_entity: null
wandb_name: null
wandb_model_log_interval: -1
detect_anomaly: false
pretrain_path: null
init_param: []
ignore_init_mismatch: true
freeze_param: []
num_iters_per_epoch: null
batch_size: 20
valid_batch_size: null
batch_bins: 25000000
valid_batch_bins: null
train_shape_file:
- exp/st_stats_raw_bpe1000_sp/train/speech_shape
- exp/st_stats_raw_bpe1000_sp/train/text_shape.bpe
- exp/st_stats_raw_bpe1000_sp/train/src_text_shape.bpe
valid_shape_file:
- exp/st_stats_raw_bpe1000_sp/valid/speech_shape
- exp/st_stats_raw_bpe1000_sp/valid/text_shape.bpe
- exp/st_stats_raw_bpe1000_sp/valid/src_text_shape.bpe
batch_type: numel
valid_batch_type: null
fold_length:
- 80000
- 150
- 150
sort_in_batch: descending
sort_batch: descending
multiple_iterator: false
chunk_length: 500
chunk_shift_ratio: 0.5
num_cache_chunks: 1024
train_data_path_and_name_and_type:
-   - dump/raw/train_sp/wav.scp
    - speech
    - kaldi_ark
-   - dump/raw/train_sp/text.tc.en
    - text
    - text
-   - dump/raw/train_sp/text.tc.rm.ta
    - src_text
    - text
valid_data_path_and_name_and_type:
-   - dump/raw/dev/wav.scp
    - speech
    - kaldi_ark
-   - dump/raw/dev/text.tc.en
    - text
    - text
-   - dump/raw/dev/text.tc.rm.ta
    - src_text
    - text
allow_variable_data_keys: false
max_cache_size: 0.0
max_cache_fd: 32
valid_max_cache_size: null
optim: adam
optim_conf:
    lr: 0.002
    weight_decay: 1.0e-06
scheduler: warmuplr
scheduler_conf:
    warmup_steps: 15000
token_list:
- <blank>
- <unk>
- s
- ▁
- apo
- '&'
- ;
- ▁i
- ▁you
- t
- ▁it
- ▁the
- ▁and
- ▁to
- ▁that
- ▁a
- n
- a
- ▁he
- ▁me
- m
- d
- ▁yes
- ▁she
- ▁no
- ▁in
- ▁what
- ▁for
- ▁we
- ing
- ll
- ▁they
- re
- ▁are
- ▁did
- ▁god
- ▁is
- e
- ed
- ▁so
- ▁her
- ▁do
- ▁have
- ▁of
- ▁with
- ▁go
- ▁know
- ▁not
- ▁was
- ▁on
- ▁don
- y
- ▁him
- ▁one
- ▁like
- ▁there
- '%'
- ▁pw
- ▁be
- ▁at
- ▁told
- ▁good
- ▁will
- ▁my
- ▁all
- ▁or
- c
- er
- p
- ▁how
- ▁ah
- r
- ▁but
- ▁them
- ▁see
- ▁get
- ▁can
- i
- ▁when
- ▁going
- ▁about
- ▁mean
- ▁this
- k
- ▁your
- ▁by
- ▁if
- u
- ▁come
- ▁up
- ▁tell
- g
- ▁said
- ▁then
- ▁now
- ▁yeah
- o
- ▁out
- al
- ra
- ▁because
- ▁time
- ▁well
- ▁would
- ▁p
- ▁from
- h
- ar
- f
- ▁swear
- ▁went
- b
- ▁really
- or
- ▁want
- ri
- ▁home
- ▁work
- ve
- ▁take
- ▁got
- ▁just
- l
- ▁uh
- ▁why
- en
- ▁even
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- ▁day
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- ly
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- ▁oh
- ▁doing
- ▁everything
- ▁here
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- ▁two
- ▁anyway
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- ▁still
- ▁say
- ro
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- w
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- ▁girl
- ▁f
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- ▁too
- ▁let
- ▁understand
- ▁may
- ▁much
- ▁think
- ch
- ir
- ha
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- ▁tomorrow
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- ▁people
- es
- ▁year
- di
- ba
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- el
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- ▁house
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- un
- ▁an
- ▁give
- ▁only
- ▁better
- pe
- ▁need
- ▁buy
- ▁de
- ne
- ▁ha
- ur
- ion
- ▁made
- la
- ▁willing
- ▁nothing
- ▁called
- ▁night
- ▁yesterday
- se
- ▁came
- ▁lot
- ter
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- ▁eat
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- ▁put
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- ▁those
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- ▁ok
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- fa
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- vi
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- ▁thought
- ▁also
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- ▁bring
- ▁bit
- ▁lo
- ▁leave
- ▁man
- ▁left
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- ▁week
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- ▁fun
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- co
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- ▁brother
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- gh
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- ▁dear
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- ▁dinner
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- and
- ▁pass
- ▁hot
- ▁guy
- ▁least
- ▁down
- ▁bought
- ▁dinars
- ▁working
- ▁around
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- ▁poor
- ▁stuff
- ▁hope
- ▁used
- ▁again
- ▁bro
- ul
- ▁phone
- ▁ex
- ▁done
- ▁six
- ▁na
- ▁month
- ▁tired
- ▁check
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- oo
- ▁later
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- ▁five
- ▁watch
- ya
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- ment
- ut
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- ▁great
- ▁daughter
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- side
- ▁change
- ▁yet
- ting
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- ▁honestly
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- ol
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- ▁sure
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- ▁spend
- ▁exactly
- ▁boy
- ▁course
- ▁end
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- ▁family
- ▁asked
- ▁enough
- ▁during
- ▁rest
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- ▁gave
- ▁true
- ▁while
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- ▁away
- ▁kids
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- ▁twenty
- ▁eight
- ▁someone
- ▁cha
- ▁clothes
- ah
- ▁myself
- ▁nice
- ▁late
- ▁old
- ▁real
- age
- ant
- ▁fast
- ▁add
- ▁hard
- ▁these
- ful
- im
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- ▁salad
- ▁win
- ▁everyone
- ▁water
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- ▁remember
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- ▁minute
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- ▁sunday
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- ▁shop
- ▁cold
- ▁meet
- ▁wear
- ever
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- tic
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- ▁beach
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- ight
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- ▁thursday
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- <sos/eos>
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- ▁يحب
- ▁تف
- ▁أهلا
- وف
- ▁غدوة
- ▁بيك
- ▁بد
- عن
- ▁در
- ▁ننج
- هار
- ▁الحكاية
- مون
- وق
- ▁نورمال
- ▁عندها
- خر
- ▁بو
- ▁حب
- ▁آكا
- ▁وف
- ▁هاذيكا
- ▁ديجا
- ▁وق
- ▁طي
- لتل
- بعث
- ▁تص
- رك
- ▁مانيش
- ▁العادة
- ▁شوف
- ضر
- ▁يمشي
- ▁نعملوا
- ▁عرفت
- ▁زال
- ▁متع
- ▁عمل
- ▁بيها
- ▁نحكي
- اع
- ▁نج
- معة
- ▁والكل
- عناها
- ▁يعي
- ▁نجي
- ستن
- ▁هاذيك
- ▁عام
- ▁فلوس
- قة
- تين
- ▁بالقدا
- لهم
- ▁تخدم
- ▁ٱ
- ▁شيء
- ▁راهي
- ▁جاب
- ولاد
- ابل
- ▁ماك
- عة
- ▁نمشيوا
- وني
- شري
- بار
- انس
- ▁وقتها
- ▁جديد
- ▁يز
- ▁كر
- ▁حاسيلو
- ▁شق
- ▁اه
- ▁سايي
- ▁انشالل
- رج
- مني
- ▁بلا
- ▁صحيح
- ▁غير
- ▁يخدم
- مان
- وكا
- ▁عند
- ▁قاعدة
- ▁تس
- ربة
- ▁راس
- ▁حط
- ▁نكل
- تني
- ▁الو
- سيون
- ▁عندنا
- ▁لو
- ▁ست
- صف
- ▁ض
- ▁كامل
- ▁نخدم
- ▁يبدا
- ▁دونك
- ▁أمور
- رات
- ▁تونس
- بدا
- ▁تحكي
- ▁سو
- ▁جاي
- ▁وحدة
- ▁ساعة
- حنا
- ▁بكري
- ▁إل
- ▁وبر
- ▁كم
- ▁تبدا
- ارة
- ادي
- رق
- لوا
- ▁يمكن
- ▁خاط
- ▁وص
- جين
- ▁هاذاي
- ▁هز
- قد
- ▁قل
- ▁وكهو
- ▁نص
- ▁دي
- لقى
- ▁وأنا
- سين
- ▁يح
- ▁ماشي
- ▁شو
- ▁خذيت
- امات
- ▁كنت
- خرج
- ▁لقيت
- رتاح
- كس
- ▁حاجات
- ▁مريق
- ▁مل
- ليفون
- اوا
- ▁شفت
- ▁عاملة
- ▁تن
- ▁والا
- سأل
- ▁حد
- ▁قاللك
- ▁العباد
- ▁عالاخ
- ▁وآك
- ▁ماني
- ▁ناخذ
- ▁حم
- ▁الإ
- ▁ماضي
- ▁ث
- الة
- ▁أخرى
- رين
- ▁تشوف
- ▁نخرج
- ▁أربعة
- ▁ألف
- نيش
- ▁هاي
- آ
- ▁فيك
- رشة
- ولة
- فلة
- ▁بابا
- ▁أما
- ▁روحي
- ▁فيهم
- ▁رج
- ▁ليك
- ونس
- يرة
- ▁وأكهو
- ندي
- ▁صار
- شك
- ▁نرو
- ▁آكهو
- ▁تش
- ▁غاديكا
- ▁معاها
- ▁لب
- ▁أذاكا
- ▁آني
- ▁يوم
- عملوا
- ▁نقعد
- دوا
- ▁عد
- سمع
- متني
- ▁الخدمة
- ▁مازلت
- ▁قعدت
- ايا
- ▁برك
- قعد
- ▁خرجت
- ضح
- ▁قالل
- ▁يقول
- ▁وفي
- ▁حق
- ختي
- ▁يعني
- خدم
- ▁جيت
- ▁نرمال
- طف
- ▁عجب
- ▁تقعد
- ▁مشينا
- اية
- ▁خدمة
- لدي
- روف
- ▁الفطر
- ▁مشكل
- ▁سل
- ▁وآنا
- الط
- ▁بالس
- ▁هانا
- ▁أوه
- ▁أذيكا
- ▁وإ
- ▁عليهم
- ▁حالة
- جت
- قضي
- ▁لق
- ▁ونصف
- سعة
- عطيه
- عاو
- خانة
- ▁مخ
- ▁شبيك
- بيعة
- ▁أهوك
- يني
- ▁تعد
- ▁خال
- ▁قريب
- ▁راك
- ▁قالت
- ▁لتو
- ▁أكثر
- اعة
- ▁يظهرلي
- ▁ماشية
- سمعني
- ▁نسيت
- ▁ينج
- ▁الحمدلل
- هدي
- ▁وشن
- ▁تطي
- ▁هنا
- ▁نسمع
- ▁إنتوما
- ▁نحكيلك
- ▁قاعد
- ▁اسمعني
- خرين
- إ
- ماعة
- ▁بالر
- ▁دا
- ▁عمر
- ▁نشري
- ▁قهوة
- ▁تبارك
- ▁صب
- ▁مشات
- غر
- ▁شريت
- ▁عامل
- ▁زوج
- ثنين
- ▁برب
- ريق
- ▁نكم
- ▁لم
- بيب
- ▁مياة
- ▁مالل
- ▁قعد
- ▁سخون
- قس
- ▁وحده
- ▁اسمع
- ▁خمسة
- ▁غالي
- ▁الأو
- رلي
- ▁العظيم
- ▁ترو
- تهم
- كري
- ▁نجيب
- ▁جملة
- قول
- ▁قلتلي
- ▁إيجا
- ▁يقعد
- ▁إيام
- ▁يعطيك
- ▁نخل
- ▁دب
- يمة
- رهبة
- ▁نهز
- ▁محم
- ▁بين
- غار
- ▁نحنا
- ▁بون
- ▁الغ
- ▁شهر
- ▁بار
- رقة
- ▁نطي
- ئ
- ترو
- ▁ملا
- ▁الكرهبة
- ▁باه
- ▁عالإخ
- ▁عباد
- ▁بلاصة
- ▁مشى
- بيع
- ▁نفس
- ▁عملنا
- ▁واح
- ▁أحلاه
- ▁بحذاك
- ▁لأ
- ▁دخ
- باب
- ▁ودر
- ▁غالب
- ▁ناكل
- ▁مثلا
- ء
- ▁راقد
- ▁تفر
- ▁الوقت
- ▁تاخذ
- حذا
- نتر
- ▁نبدا
- ▁حال
- ▁مريم
- الم
- ▁جمعة
- رجول
- ▁معايا
- ▁تخرج
- ▁باس
- ▁ساعات
- ▁عندهم
- ▁نتفر
- مسة
- ▁الجمعة
- بعين
- ▁أكاهو
- ▁ميش
- مراة
- ▁خذا
- ▁ظ
- ▁سيدي
- ▁معاي
- ▁شبيه
- ▁حكا
- ▁سف
- ▁بعضنا
- ▁بالض
- ▁ليلة
- ▁زعما
- ▁الحق
- مضان
- ▁صعيب
- ▁قالتلك
- ً
- ملة
- ▁بق
- عرف
- لاطة
- ▁خرج
- ▁أخت
- ▁تقوللي
- ▁معانا
- ▁صغير
- ▁إسمه
- ▁بعض
- ▁العام
- ▁علينا
- ▁يتع
- ▁فاش
- ▁شع
- ▁معاهم
- ▁يسالش
- ▁لهنا
- ▁سمعت
- ▁البار
- ▁نتصو
- ▁الاخ
- ▁وكان
- وبة
- دمة
- ▁كون
- ▁مبعد
- ▁تسمع
- ▁بعيد
- ▁تاكل
- ▁نلقا
- لامة
- لاثة
- ▁ذ
- ▁تحس
- ▁الواح
- ▁لدار
- ▁فاتت
- ▁تاو
- ▁أحوالك
- ▁عاملين
- ▁كبيرة
- عجب
- ▁بنت
- ▁بيدي
- ▁حكيت
- ▁تحط
- ▁مسكينة
- ▁هاذوكم
- ▁نزيد
- لاث
- ▁عشرة
- ▁عيني
- ▁تعب
- ▁ياكل
- ▁وزيد
- ▁طول
- ▁حمدلله
- ▁وقتاه
- ▁معناه
- ▁وآش
- ▁ووه
- ▁وواحد
- ▁نشوفوا
- ▁عيد
- ▁بصراحة
- ▁بحذانا
- ▁قاعدين
- ▁راجل
- ▁وحدي
- ▁وعشرين
- ▁لين
- ▁خايب
- ▁قالتله
- ▁تهز
- عيد
- ▁كبير
- ▁يعرف
- ▁عارف
- ▁الفلوس
- ▁زايد
- ▁خدمت
- ▁هاذوما
- ▁سلاطة
- ▁فارغة
- ▁ساعتين
- ▁تبد
- ▁راو
- ▁مائة
- ▁بعضهم
- ▁ظاهرلي
- ▁الفازة
- كتب
- ▁القهوة
- سبوك
- ▁زاد
- ▁ضرب
- حكيلي
- ▁فوق
- ▁عاود
- ▁راي
- ▁ومبعد
- ▁حوايج
- ▁دخلت
- ▁يقوللك
- ▁زيد
- ▁زلت
- لفزة
- ▁وقال
- ▁يهب
- ▁يلزمني
- ▁الحمد
- ▁أذي
- طبيعت
- ▁دورة
- ▁عالأقل
- ▁آذاك
- ▁وبال
- ▁الجاي
- عطيني
- ▁ياخذ
- ▁احكيلي
- ▁نهبط
- ▁رقدت
- بلاصة
- ▁عزيز
- ▁صغار
- ▁أقسم
- ▁جيب
- ▁وصلت
- ▁أحوال
- ▁جيست
- ▁جماعة
- سئل
- ▁خوذ
- ▁يهز
- ▁الأخرى
- ▁آلاف
- ▁إسمع
- ▁الحقيقة
- ▁ناقص
- ▁حاط
- ▁موجود
- عباد
- ▁آذيك
- ▁خارج
- ▁الخير
- ▁البنات
- بقى
- ▁طرف
- ▁سينون
- ▁ماذاب
- ▁البحر
- ▁نرقد
- مدلله
- ▁إيجى
- ▁خالتي
- ▁فازة
- ▁بريك
- ▁شريبتك
- ▁تطلع
- ؤ
- ▁المشكلة
- ▁طري
- ▁مادام
- ▁طلبت
- ▁يلعب
- ▁نعاود
- ▁وحدك
- ▁ظاهر
- ٱ
- ژ
- ٍ
- <sos/eos>
init: null
input_size: null
ctc_conf:
    dropout_rate: 0.0
    ctc_type: builtin
    reduce: true
    ignore_nan_grad: true
model_conf:
    asr_weight: 0.3
    mt_weight: 0.0
    mtlalpha: 1.0
    lsm_weight: 0.1
    length_normalized_loss: false
use_preprocessor: true
token_type: bpe
src_token_type: bpe
bpemodel: data/token_list/tgt_bpe_unigram1000/bpe.model
src_bpemodel: data/token_list/src_bpe_unigram1000/bpe.model
non_linguistic_symbols: null
cleaner: null
g2p: null
speech_volume_normalize: null
rir_scp: null
rir_apply_prob: 1.0
noise_scp: null
noise_apply_prob: 1.0
noise_db_range: '13_15'
frontend: default
frontend_conf:
    n_fft: 512
    hop_length: 256
    fs: 16k
specaug: specaug
specaug_conf:
    apply_time_warp: true
    time_warp_window: 5
    time_warp_mode: bicubic
    apply_freq_mask: true
    freq_mask_width_range:
    - 0
    - 27
    num_freq_mask: 2
    apply_time_mask: true
    time_mask_width_ratio_range:
    - 0.0
    - 0.05
    num_time_mask: 5
normalize: global_mvn
normalize_conf:
    stats_file: exp/st_stats_raw_bpe1000_sp/train/feats_stats.npz
preencoder: null
preencoder_conf: {}
encoder: conformer
encoder_conf:
    output_size: 256
    attention_heads: 4
    linear_units: 1024
    num_blocks: 12
    dropout_rate: 0.1
    positional_dropout_rate: 0.1
    attention_dropout_rate: 0.1
    input_layer: conv2d
    normalize_before: true
    macaron_style: true
    rel_pos_type: latest
    pos_enc_layer_type: rel_pos
    selfattention_layer_type: rel_selfattn
    activation_type: swish
    use_cnn_module: true
    cnn_module_kernel: 31
postencoder: null
postencoder_conf: {}
decoder: transformer
decoder_conf:
    attention_heads: 4
    linear_units: 2048
    num_blocks: 6
    dropout_rate: 0.1
    positional_dropout_rate: 0.1
    self_attention_dropout_rate: 0.1
    src_attention_dropout_rate: 0.1
extra_asr_decoder: transformer
extra_asr_decoder_conf:
    input_layer: embed
    num_blocks: 2
    linear_units: 2048
    dropout_rate: 0.1
extra_mt_decoder: transformer
extra_mt_decoder_conf:
    input_layer: embed
    num_blocks: 2
    linear_units: 2048
    dropout_rate: 0.1
required:
- output_dir
- src_token_list
- token_list
version: 0.10.6a1
distributed: false
```

</details>

### Citing ESPnet

```BibTex
@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}

```

or arXiv:

```bibtex
@misc{watanabe2018espnet,
  title={ESPnet: End-to-End Speech Processing Toolkit},
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  year={2018},
  eprint={1804.00015},
  archivePrefix={arXiv},
  primaryClass={cs.CL}
}
```


---
tags:
- espnet
- audio
- speech-enhancement
- audio-to-audio
language: en
datasets:
- wsj0_2mix
license: cc-by-4.0
---
## Example ESPnet2 ENH model
### `Chenda_Li/wsj0_2mix_enh_train_enh_rnn_tf_raw_valid.si_snr.ave`
♻ Imported from https://zenodo.org/record/4498554/

This model was trained by Chenda Li using wsj0_2mix/enh1 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
```python
# coming soon
```
### Citing ESPnet
```BibTex
@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}
@inproceedings{hayashi2020espnet,
  title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit},
  author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu},
  booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={7654--7658},
  year={2020},
  organization={IEEE}
}
```
or arXiv:
```bibtex
@misc{watanabe2018espnet,
      title={ESPnet: End-to-End Speech Processing Toolkit},
      author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
      year={2018},
      eprint={1804.00015},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```


---
tags:
- espnet
- audio
- text-to-speech
language: ja
datasets:
- jsut
license: cc-by-4.0
---
## Example ESPnet2 TTS model
### `kan-bayashi/jsut_tts_train_conformer_fastspeech2_tacotron2_teacher_raw_phn_jaconv_pyopenjtalk_accent_with_pause_train.loss.ave`
♻ Imported from https://zenodo.org/record/4436448/

This model was trained by kan-bayashi using jsut/tts1 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
```python
# coming soon
```
### Citing ESPnet
```BibTex
@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}
@inproceedings{hayashi2020espnet,
  title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit},
  author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu},
  booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={7654--7658},
  year={2020},
  organization={IEEE}
}
```
or arXiv:
```bibtex
@misc{watanabe2018espnet,
      title={ESPnet: End-to-End Speech Processing Toolkit},
      author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
      year={2018},
      eprint={1804.00015},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```


---
tags:
- espnet
- audio
- text-to-speech
language: en
datasets:
- libritts
license: cc-by-4.0
---
## Example ESPnet2 TTS model
### `kan-bayashi/libritts_tts_train_xvector_trasnformer_raw_phn_tacotron_g2p_en_no_space_train.loss.ave`
♻ Imported from https://zenodo.org/record/4409704/

This model was trained by kan-bayashi using libritts/tts1 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
```python
# coming soon
```
### Citing ESPnet
```BibTex
@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}
@inproceedings{hayashi2020espnet,
  title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit},
  author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu},
  booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={7654--7658},
  year={2020},
  organization={IEEE}
}
```
or arXiv:
```bibtex
@misc{watanabe2018espnet,
      title={ESPnet: End-to-End Speech Processing Toolkit},
      author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
      year={2018},
      eprint={1804.00015},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```


---
tags:
- espnet
- audio
- text-to-speech
language: en
datasets:
- vctk
license: cc-by-4.0
---
## Example ESPnet2 TTS model
### `kan-bayashi/vctk_gst_tacotron2`
♻ Imported from https://zenodo.org/record/3986237/

This model was trained by kan-bayashi using vctk/tts1 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
```python
# coming soon
```
### Citing ESPnet
```BibTex
@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}
@inproceedings{hayashi2020espnet,
  title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit},
  author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu},
  booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={7654--7658},
  year={2020},
  organization={IEEE}
}
```
or arXiv:
```bibtex
@misc{watanabe2018espnet,
      title={ESPnet: End-to-End Speech Processing Toolkit},
      author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
      year={2018},
      eprint={1804.00015},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```


---
tags:
- espnet
- audio
- text-to-speech
language: ja
datasets:
- jsut
license: cc-by-4.0
---
## ESPnet2 TTS pretrained model
### `kan-bayashi/jsut_full_band_vits_prosody`
♻ Imported from https://zenodo.org/record/5521340/

This model was trained by kan-bayashi using jsut/tts1 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
```python
# coming soon
```
### Citing ESPnet
```BibTex
@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}
@inproceedings{hayashi2020espnet,
  title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit},
  author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu},
  booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={7654--7658},
  year={2020},
  organization={IEEE}
}
```
or arXiv:
```bibtex
@misc{watanabe2018espnet,
      title={ESPnet: End-to-End Speech Processing Toolkit},
      author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
      year={2018},
      eprint={1804.00015},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```


---
tags:
- espnet
- audio
- text-to-speech
language: ja
datasets:
- jsut
license: cc-by-4.0
---
## Example ESPnet2 TTS model
### `kan-bayashi/jsut_tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_accent_train.loss.ave`
♻ Imported from https://zenodo.org/record/4381098/

This model was trained by kan-bayashi using jsut/tts1 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
```python
# coming soon
```
### Citing ESPnet
```BibTex
@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}
@inproceedings{hayashi2020espnet,
  title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit},
  author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu},
  booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={7654--7658},
  year={2020},
  organization={IEEE}
}
```
or arXiv:
```bibtex
@misc{watanabe2018espnet,
      title={ESPnet: End-to-End Speech Processing Toolkit},
      author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
      year={2018},
      eprint={1804.00015},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```


---
tags:
- espnet
- audio
- automatic-speech-recognition
language: en
datasets:
- chime4
license: cc-by-4.0
---
## Example ESPnet2 ASR model
### `kamo-naoyuki/chime4_asr_train_asr_transformer3_raw_en_char_sp_valid.acc.ave`
♻ Imported from https://zenodo.org/record/4414883/

This model was trained by kamo-naoyuki using chime4/asr1 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
```python
# coming soon
```
### Citing ESPnet
```BibTex
@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}
@inproceedings{hayashi2020espnet,
  title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit},
  author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu},
  booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={7654--7658},
  year={2020},
  organization={IEEE}
}
```
or arXiv:
```bibtex
@misc{watanabe2018espnet,
      title={ESPnet: End-to-End Speech Processing Toolkit},
      author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
      year={2018},
      eprint={1804.00015},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```


---
tags:
- espnet
- audio
- speech-translation
language: noinfo
datasets:
- iwslt22_dialect
license: cc-by-4.0
---

## ESPnet2 ST model

### `espnet/brianyan918_iwslt22_dialect_st_transformer_fisherlike_4gpu_bbins16m_fix`

This model was trained by Brian Yan using iwslt22_dialect recipe in [espnet](https://github.com/espnet/espnet/).

### Demo: How to use in ESPnet2

```bash
cd espnet
git checkout 77fce65312877a132bbae01917ad26b74f6e2e14
pip install -e .
cd egs2/iwslt22_dialect/st1
./run.sh --skip_data_prep false --skip_train true --download_model espnet/brianyan918_iwslt22_dialect_st_transformer_fisherlike_4gpu_bbins16m_fix
```

<!-- Generated by scripts/utils/show_st_results.sh -->
# RESULTS
## Environments
- date: `Tue Feb  8 13:29:21 EST 2022`
- python version: `3.8.12 (default, Oct 12 2021, 13:49:34)  [GCC 7.5.0]`
- espnet version: `espnet 0.10.7a1`
- pytorch version: `pytorch 1.8.1`
- Git hash: `77fce65312877a132bbae01917ad26b74f6e2e14`
  - Commit date: `Tue Feb 8 10:48:10 2022 -0500`

## st_transformer_fisherlike_4gpu_bbins16m_fix_raw_bpe_tc1000_sp
### BLEU

|dataset|bleu_score|verbose_score|
|---|---|---|
p3_st_model_valid.acc.ave|12.0|37.4/17.3/8.6/4.5 (BP = 0.952 ratio = 0.953 hyp_len = 40192 ref_len = 42181)

## ST config

<details><summary>expand</summary>

```
config: conf/tuning/transformer_fisherlike_4gpu_bbins16m_fix.yaml
print_config: false
log_level: INFO
dry_run: false
iterator_type: sequence
output_dir: exp/st_transformer_fisherlike_4gpu_bbins16m_fix_raw_bpe_tc1000_sp
ngpu: 1
seed: 0
num_workers: 1
num_att_plot: 3
dist_backend: nccl
dist_init_method: env://
dist_world_size: 4
dist_rank: 0
local_rank: 0
dist_master_addr: localhost
dist_master_port: 36641
dist_launcher: null
multiprocessing_distributed: true
unused_parameters: false
sharded_ddp: false
cudnn_enabled: true
cudnn_benchmark: false
cudnn_deterministic: true
collect_stats: false
write_collected_feats: false
max_epoch: 50
patience: null
val_scheduler_criterion:
- valid
- loss
early_stopping_criterion:
- valid
- loss
- min
best_model_criterion:
-   - valid
    - acc
    - max
keep_nbest_models: 10
nbest_averaging_interval: 0
grad_clip: 3
grad_clip_type: 2.0
grad_noise: false
accum_grad: 2
no_forward_run: false
resume: true
train_dtype: float32
use_amp: false
log_interval: null
use_matplotlib: true
use_tensorboard: true
use_wandb: false
wandb_project: null
wandb_id: null
wandb_entity: null
wandb_name: null
wandb_model_log_interval: -1
detect_anomaly: false
pretrain_path: null
init_param: []
ignore_init_mismatch: false
freeze_param: []
num_iters_per_epoch: null
batch_size: 20
valid_batch_size: null
batch_bins: 16000000
valid_batch_bins: null
train_shape_file:
- exp/st_stats_raw_bpe1000_sp/train/speech_shape
- exp/st_stats_raw_bpe1000_sp/train/text_shape.bpe
- exp/st_stats_raw_bpe1000_sp/train/src_text_shape.bpe
valid_shape_file:
- exp/st_stats_raw_bpe1000_sp/valid/speech_shape
- exp/st_stats_raw_bpe1000_sp/valid/text_shape.bpe
- exp/st_stats_raw_bpe1000_sp/valid/src_text_shape.bpe
batch_type: numel
valid_batch_type: null
fold_length:
- 80000
- 150
- 150
sort_in_batch: descending
sort_batch: descending
multiple_iterator: false
chunk_length: 500
chunk_shift_ratio: 0.5
num_cache_chunks: 1024
train_data_path_and_name_and_type:
-   - /scratch/iwslt22dump//raw/train_sp/wav.scp
    - speech
    - kaldi_ark
-   - /scratch/iwslt22dump//raw/train_sp/text.tc.en
    - text
    - text
-   - /scratch/iwslt22dump//raw/train_sp/text.tc.rm.ta
    - src_text
    - text
valid_data_path_and_name_and_type:
-   - /scratch/iwslt22dump//raw/dev/wav.scp
    - speech
    - kaldi_ark
-   - /scratch/iwslt22dump//raw/dev/text.tc.en
    - text
    - text
-   - /scratch/iwslt22dump//raw/dev/text.tc.rm.ta
    - src_text
    - text
allow_variable_data_keys: false
max_cache_size: 0.0
max_cache_fd: 32
valid_max_cache_size: null
optim: adam
optim_conf:
    lr: 12.5
scheduler: noamlr
scheduler_conf:
    model_size: 256
    warmup_steps: 25000
token_list:
- <blank>
- <unk>
- s
- ▁
- apo
- '&'
- ;
- ▁i
- ▁you
- t
- ▁it
- ▁the
- ▁and
- ▁to
- ▁that
- ▁a
- n
- a
- ▁he
- ▁me
- m
- d
- ▁yes
- ▁she
- ▁no
- ▁in
- ▁what
- ▁for
- ▁we
- ing
- ll
- ▁they
- re
- ▁are
- ▁did
- ▁god
- ▁is
- e
- ed
- ▁so
- ▁her
- ▁do
- ▁have
- ▁of
- ▁with
- ▁go
- ▁know
- ▁not
- ▁was
- ▁on
- ▁don
- y
- ▁him
- ▁one
- ▁like
- ▁there
- '%'
- ▁pw
- ▁be
- ▁at
- ▁told
- ▁good
- ▁will
- ▁my
- ▁all
- ▁or
- c
- er
- p
- ▁how
- ▁ah
- r
- ▁but
- ▁them
- ▁see
- ▁get
- ▁can
- i
- ▁when
- ▁going
- ▁about
- ▁mean
- ▁this
- k
- ▁your
- ▁by
- ▁if
- u
- ▁come
- ▁up
- ▁tell
- g
- ▁said
- ▁then
- ▁now
- ▁yeah
- o
- ▁out
- al
- ra
- ▁because
- ▁time
- ▁well
- ▁would
- ▁p
- ▁from
- h
- ar
- f
- ▁swear
- ▁went
- b
- ▁really
- or
- ▁want
- ri
- ▁home
- ▁work
- ve
- ▁take
- ▁got
- ▁just
- l
- ▁uh
- ▁why
- en
- ▁even
- ▁am
- ▁who
- ▁make
- ▁day
- '-'
- in
- ▁something
- ▁some
- ou
- ▁us
- ▁okay
- ▁where
- ▁does
- ▁has
- ▁thank
- ▁c
- ▁his
- th
- ▁back
- ▁fine
- ▁today
- ly
- ▁b
- ▁oh
- ▁doing
- ▁everything
- ▁here
- le
- ▁thing
- ▁two
- ▁anyway
- li
- ▁had
- ▁still
- ▁say
- ro
- ▁after
- ce
- ▁hello
- ▁ma
- ▁call
- w
- ▁listen
- il
- ▁should
- ▁girl
- ▁f
- z
- ▁too
- ▁let
- ▁understand
- ▁may
- ▁much
- ▁think
- ch
- ir
- ha
- ▁other
- ▁tomorrow
- ▁were
- ▁people
- es
- ▁year
- di
- ba
- ▁right
- el
- ▁things
- ▁house
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- ▁actually
- un
- ▁an
- ▁give
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- ▁better
- pe
- ▁need
- ▁buy
- ▁de
- ne
- ▁ha
- ur
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- la
- ▁willing
- ▁nothing
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- se
- ▁came
- ▁lot
- ter
- ▁g
- po
- ▁find
- ry
- ▁car
- ▁over
- ic
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- ent
- ▁always
- ▁very
- 'on'
- ▁put
- ▁ramadan
- ▁those
- ▁hear
- is
- ▁talk
- ▁three
- ▁anything
- ▁mo
- ▁little
- ▁been
- ▁already
- fi
- ation
- ke
- ▁first
- ▁look
- it
- ▁won
- ▁mom
- ▁way
- ▁before
- ▁ok
- ▁last
- fa
- ▁cook
- vi
- ▁hi
- ▁same
- ▁thought
- ▁also
- um
- ate
- ▁money
- ▁start
- ▁place
- us
- ▁morning
- ▁could
- ▁ask
- ▁bring
- ▁bit
- ▁lo
- ▁leave
- ▁man
- ▁left
- ine
- ▁days
- ge
- ▁la
- ▁week
- ▁friend
- ▁problem
- ▁sister
- ▁allah
- ▁feel
- ▁every
- ▁more
- fe
- ▁long
- ▁hundred
- ▁j
- ▁eh
- ho
- ca
- em
- ▁talking
- ▁exam
- ▁next
- ▁new
- ▁fun
- ▁took
- ▁alright
- co
- ▁w
- ▁um
- ▁eid
- ▁brother
- ▁our
- gh
- ow
- ▁o
- ▁four
- ni
- wa
- ▁else
- ▁finish
- bo
- ▁sleep
- ▁bless
- ▁dear
- ▁since
- ▁play
- ▁name
- hi
- ▁coming
- ▁many
- et
- ▁usual
- ▁con
- ▁maybe
- ▁off
- bi
- ▁than
- ▁any
- ▁mother
- ▁son
- om
- ▁their
- ▁keep
- ▁dinner
- ▁ten
- ▁half
- ▁help
- ▁bad
- and
- ▁pass
- ▁hot
- ▁guy
- ▁least
- ▁down
- ▁bought
- ▁dinars
- ▁working
- ▁around
- ▁normal
- ▁poor
- ▁stuff
- ▁hope
- ▁used
- ▁again
- ▁bro
- ul
- ▁phone
- ▁ex
- ▁done
- ▁six
- ▁na
- ▁month
- ▁tired
- ▁check
- ▁show
- ▁together
- oo
- ▁later
- ▁past
- ▁five
- ▁watch
- ya
- ▁coffee
- ment
- ut
- ▁plan
- ▁great
- ▁daughter
- j
- ▁another
- side
- ▁change
- ▁yet
- ting
- ▁until
- ▁honestly
- ▁whole
- ol
- ▁care
- ▁sure
- able
- id
- ▁big
- ▁spend
- ▁exactly
- ▁boy
- ▁course
- ▁end
- ▁please
- ▁started
- he
- up
- ▁found
- ▁saw
- ▁family
- ▁asked
- ▁enough
- ▁during
- ▁rest
- ▁which
- ▁gave
- ▁true
- ▁while
- ▁job
- ▁el
- ▁each
- ▁away
- ▁kids
- ▁goes
- less
- ▁twenty
- ▁eight
- ▁someone
- ▁cha
- ▁clothes
- ah
- ▁myself
- ▁nice
- ▁late
- ▁old
- ▁real
- age
- ant
- ▁fast
- ▁add
- ▁hard
- ▁these
- ful
- im
- ▁close
- ive
- ▁dad
- ▁pay
- ies
- ▁dude
- ▁alone
- ▁far
- ance
- ▁dis
- ▁seven
- ▁isn
- ▁pro
- our
- ▁thousand
- ▁break
- ▁hour
- ▁wait
- ▁brought
- ▁open
- ▁un
- ▁wedding
- ▁walk
- ▁father
- ▁ka
- ▁second
- x
- ▁saturday
- ▁salad
- ▁win
- ▁everyone
- ▁water
- ▁tunis
- ▁remember
- ity
- ▁wake
- ▁minute
- ▁school
- ▁sunday
- ▁own
- ▁shop
- ▁cold
- ▁meet
- ▁wear
- ever
- ▁send
- ▁early
- ▁gra
- tic
- ▁short
- ▁use
- ▁sometimes
- hou
- ▁love
- ▁prepare
- ▁sea
- ▁study
- ure
- ▁com
- qui
- ▁hand
- ▁both
- ja
- ▁summer
- ▁wrong
- ▁wanted
- che
- ▁miss
- ▁try
- ▁iftar
- ▁yourself
- q
- ▁live
- war
- ▁expensive
- ▁getting
- ▁waiting
- ▁once
- ▁kh
- ▁forgot
- ▁nine
- ▁anymore
- ▁soup
- ▁uncle
- ▁beach
- ▁saying
- ▁into
- ▁having
- ▁brik
- ▁room
- ▁food
- ▁visit
- ▁matter
- ▁thirty
- ▁taking
- ▁rain
- ▁aunt
- ▁never
- ▁pick
- ▁tunisia
- ▁health
- ▁head
- ▁cut
- ▁fasting
- ▁sick
- ▁friday
- ▁forget
- ▁monday
- ▁become
- ▁dress
- ated
- ▁most
- wi
- ▁hang
- ▁life
- ▁fish
- ▁happy
- ▁delicious
- ▁deal
- ▁finished
- ble
- ▁studying
- ▁weather
- ▁making
- ▁cost
- ▁bl
- ▁stayed
- ▁guess
- ▁teach
- ▁stop
- ▁near
- ▁watching
- ▁without
- ▁imagine
- ▁seriously
- fl
- ▁speak
- ▁idea
- ▁must
- ▁normally
- ▁turn
- ize
- ▁clean
- ▁tv
- ▁meat
- ▁woke
- ▁example
- ▁easy
- ▁sent
- ▁sell
- over
- ▁fifty
- ▁amazing
- ▁beautiful
- ▁whatever
- ▁enjoy
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- ▁believe
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- ▁تفر
- ▁الوقت
- ▁تاخذ
- حذا
- نتر
- ▁نبدا
- ▁حال
- ▁مريم
- الم
- ▁جمعة
- رجول
- ▁معايا
- ▁تخرج
- ▁باس
- ▁ساعات
- ▁عندهم
- ▁نتفر
- مسة
- ▁الجمعة
- بعين
- ▁أكاهو
- ▁ميش
- مراة
- ▁خذا
- ▁ظ
- ▁سيدي
- ▁معاي
- ▁شبيه
- ▁حكا
- ▁سف
- ▁بعضنا
- ▁بالض
- ▁ليلة
- ▁زعما
- ▁الحق
- مضان
- ▁صعيب
- ▁قالتلك
- ً
- ملة
- ▁بق
- عرف
- لاطة
- ▁خرج
- ▁أخت
- ▁تقوللي
- ▁معانا
- ▁صغير
- ▁إسمه
- ▁بعض
- ▁العام
- ▁علينا
- ▁يتع
- ▁فاش
- ▁شع
- ▁معاهم
- ▁يسالش
- ▁لهنا
- ▁سمعت
- ▁البار
- ▁نتصو
- ▁الاخ
- ▁وكان
- وبة
- دمة
- ▁كون
- ▁مبعد
- ▁تسمع
- ▁بعيد
- ▁تاكل
- ▁نلقا
- لامة
- لاثة
- ▁ذ
- ▁تحس
- ▁الواح
- ▁لدار
- ▁فاتت
- ▁تاو
- ▁أحوالك
- ▁عاملين
- ▁كبيرة
- عجب
- ▁بنت
- ▁بيدي
- ▁حكيت
- ▁تحط
- ▁مسكينة
- ▁هاذوكم
- ▁نزيد
- لاث
- ▁عشرة
- ▁عيني
- ▁تعب
- ▁ياكل
- ▁وزيد
- ▁طول
- ▁حمدلله
- ▁وقتاه
- ▁معناه
- ▁وآش
- ▁ووه
- ▁وواحد
- ▁نشوفوا
- ▁عيد
- ▁بصراحة
- ▁بحذانا
- ▁قاعدين
- ▁راجل
- ▁وحدي
- ▁وعشرين
- ▁لين
- ▁خايب
- ▁قالتله
- ▁تهز
- عيد
- ▁كبير
- ▁يعرف
- ▁عارف
- ▁الفلوس
- ▁زايد
- ▁خدمت
- ▁هاذوما
- ▁سلاطة
- ▁فارغة
- ▁ساعتين
- ▁تبد
- ▁راو
- ▁مائة
- ▁بعضهم
- ▁ظاهرلي
- ▁الفازة
- كتب
- ▁القهوة
- سبوك
- ▁زاد
- ▁ضرب
- حكيلي
- ▁فوق
- ▁عاود
- ▁راي
- ▁ومبعد
- ▁حوايج
- ▁دخلت
- ▁يقوللك
- ▁زيد
- ▁زلت
- لفزة
- ▁وقال
- ▁يهب
- ▁يلزمني
- ▁الحمد
- ▁أذي
- طبيعت
- ▁دورة
- ▁عالأقل
- ▁آذاك
- ▁وبال
- ▁الجاي
- عطيني
- ▁ياخذ
- ▁احكيلي
- ▁نهبط
- ▁رقدت
- بلاصة
- ▁عزيز
- ▁صغار
- ▁أقسم
- ▁جيب
- ▁وصلت
- ▁أحوال
- ▁جيست
- ▁جماعة
- سئل
- ▁خوذ
- ▁يهز
- ▁الأخرى
- ▁آلاف
- ▁إسمع
- ▁الحقيقة
- ▁ناقص
- ▁حاط
- ▁موجود
- عباد
- ▁آذيك
- ▁خارج
- ▁الخير
- ▁البنات
- بقى
- ▁طرف
- ▁سينون
- ▁ماذاب
- ▁البحر
- ▁نرقد
- مدلله
- ▁إيجى
- ▁خالتي
- ▁فازة
- ▁بريك
- ▁شريبتك
- ▁تطلع
- ؤ
- ▁المشكلة
- ▁طري
- ▁مادام
- ▁طلبت
- ▁يلعب
- ▁نعاود
- ▁وحدك
- ▁ظاهر
- ٱ
- ژ
- ٍ
- <sos/eos>
init: null
input_size: null
ctc_conf:
    dropout_rate: 0.0
    ctc_type: builtin
    reduce: true
    ignore_nan_grad: true
model_conf:
    asr_weight: 0.3
    mt_weight: 0.0
    mtlalpha: 1.0
    lsm_weight: 0.1
    length_normalized_loss: false
use_preprocessor: true
token_type: bpe
src_token_type: bpe
bpemodel: data/token_list/tgt_bpe_unigram1000/bpe.model
src_bpemodel: data/token_list/src_bpe_unigram1000/bpe.model
non_linguistic_symbols: null
cleaner: null
g2p: null
speech_volume_normalize: null
rir_scp: null
rir_apply_prob: 1.0
noise_scp: null
noise_apply_prob: 1.0
noise_db_range: '13_15'
frontend: default
frontend_conf:
    n_fft: 512
    win_length: 400
    hop_length: 160
    fs: 16k
specaug: specaug
specaug_conf:
    apply_time_warp: true
    time_warp_window: 5
    time_warp_mode: bicubic
    apply_freq_mask: true
    freq_mask_width_range:
    - 0
    - 30
    num_freq_mask: 2
    apply_time_mask: true
    time_mask_width_range:
    - 0
    - 40
    num_time_mask: 2
normalize: global_mvn
normalize_conf:
    stats_file: exp/st_stats_raw_bpe1000_sp/train/feats_stats.npz
preencoder: null
preencoder_conf: {}
encoder: transformer
encoder_conf:
    input_layer: conv2d
    num_blocks: 12
    linear_units: 2048
    dropout_rate: 0.1
    output_size: 256
    attention_heads: 4
postencoder: null
postencoder_conf: {}
decoder: transformer
decoder_conf:
    input_layer: embed
    num_blocks: 6
    linear_units: 2048
    dropout_rate: 0.1
extra_asr_decoder: transformer
extra_asr_decoder_conf:
    input_layer: embed
    num_blocks: 2
    linear_units: 2048
    dropout_rate: 0.1
extra_mt_decoder: transformer
extra_mt_decoder_conf:
    input_layer: embed
    num_blocks: 2
    linear_units: 2048
    dropout_rate: 0.1
required:
- output_dir
- src_token_list
- token_list
version: 0.10.6a1
distributed: true
```

</details>

### Citing ESPnet

```BibTex
@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}

```

or arXiv:

```bibtex
@misc{watanabe2018espnet,
  title={ESPnet: End-to-End Speech Processing Toolkit},
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  year={2018},
  eprint={1804.00015},
  archivePrefix={arXiv},
  primaryClass={cs.CL}
}
```


---
tags:
- espnet
- audio
- automatic-speech-recognition
language: en
datasets:
- fsc
license: cc-by-4.0
---
## ESPnet2 SLU (Entity Classification) pretrained model
### `siddhana/slurp_entity_asr_train_asr_conformer_raw_en_word_valid.acc.ave_10best`
♻ Imported from https://zenodo.org/record/5590204

This model was trained by siddhana using fsc/asr1 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
```python
# coming soon
```
### Citing ESPnet
```BibTex
@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}

```
or arXiv:
```bibtex
@misc{watanabe2018espnet,
      title={ESPnet: End-to-End Speech Processing Toolkit},
      author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
      year={2018},
      eprint={1804.00015},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```


---
tags:
- espnet
- audio
- text-to-speech
language: zh
datasets:
- csmsc
license: cc-by-4.0
---
## ESPnet2 TTS pretrained model
### `kan-bayashi/csmsc_conformer_fastspeech2`
♻ Imported from https://zenodo.org/record/4031955/

This model was trained by kan-bayashi using csmsc/tts1 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
```python
# coming soon
```
### Citing ESPnet
```BibTex
@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}
@inproceedings{hayashi2020espnet,
  title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit},
  author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu},
  booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={7654--7658},
  year={2020},
  organization={IEEE}
}
```
or arXiv:
```bibtex
@misc{watanabe2018espnet,
      title={ESPnet: End-to-End Speech Processing Toolkit},
      author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
      year={2018},
      eprint={1804.00015},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```


---
tags:
- espnet
- audio
- text-to-speech
language: ja
datasets:
- jsut
license: cc-by-4.0
---
## Example ESPnet2 TTS model
### `kan-bayashi/jsut_tts_train_fastspeech2_tacotron2_teacher_raw_phn_jaconv_pyopenjtalk_accent_with_pause_train.loss.ave`
♻ Imported from https://zenodo.org/record/4436450/

This model was trained by kan-bayashi using jsut/tts1 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
```python
# coming soon
```
### Citing ESPnet
```BibTex
@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}
@inproceedings{hayashi2020espnet,
  title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit},
  author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu},
  booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={7654--7658},
  year={2020},
  organization={IEEE}
}
```
or arXiv:
```bibtex
@misc{watanabe2018espnet,
      title={ESPnet: End-to-End Speech Processing Toolkit},
      author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
      year={2018},
      eprint={1804.00015},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```


---
tags:
- espnet
- audio
- text-to-speech
language: ja
datasets:
- jsut
license: cc-by-4.0
---
## Example ESPnet2 TTS model
### `kan-bayashi/jsut_tts_train_conformer_fastspeech2_tacotron2_teacher_raw_phn_jaconv_pyopenjtalk_accent_train.loss.ave`
♻ Imported from https://zenodo.org/record/4381102/

This model was trained by kan-bayashi using jsut/tts1 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
```python
# coming soon
```
### Citing ESPnet
```BibTex
@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}
@inproceedings{hayashi2020espnet,
  title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit},
  author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu},
  booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={7654--7658},
  year={2020},
  organization={IEEE}
}
```
or arXiv:
```bibtex
@misc{watanabe2018espnet,
      title={ESPnet: End-to-End Speech Processing Toolkit},
      author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
      year={2018},
      eprint={1804.00015},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```


---
tags:
- espnet
- audio
- text-to-speech
language: zh
datasets:
- csmsc
license: cc-by-4.0
---
## Example ESPnet2 TTS model
### `kan-bayashi/csmsc_tacotron2`
♻ Imported from https://zenodo.org/record/3969118/

This model was trained by kan-bayashi using csmsc/tts1 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
```python
# coming soon
```
### Citing ESPnet
```BibTex
@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}
@inproceedings{hayashi2020espnet,
  title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit},
  author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu},
  booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={7654--7658},
  year={2020},
  organization={IEEE}
}
```
or arXiv:
```bibtex
@misc{watanabe2018espnet,
      title={ESPnet: End-to-End Speech Processing Toolkit},
      author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
      year={2018},
      eprint={1804.00015},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```