Spaces:
Runtime error
Runtime error
Update language list (#1)
Browse files- Update language list (c105fbb6baa8436dc0a9c4521d9b9d137d404809)
- Fix the language list (a71e647e9f4a4c7d4611c3728c7fd7fb0b94768f)
Co-authored-by: hysts <hysts@users.noreply.huggingface.co>
- app.py +48 -16
- lang_list.py +254 -0
- mlg_config.json +0 -186
app.py
CHANGED
@@ -1,4 +1,3 @@
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-
import json
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import os
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import gradio as gr
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@@ -7,11 +6,15 @@ import torch
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import torchaudio
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from seamless_communication.models.inference.translator import Translator
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-
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lang_idx_map = json.loads(f.read())
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LANGUAGES = lang_idx_map["multilingual"].keys()
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TASK_NAMES = [
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"S2ST (Speech to Speech translation)",
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@@ -24,6 +27,8 @@ TASK_NAMES = [
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AUDIO_SAMPLE_RATE = 16000.0
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MAX_INPUT_AUDIO_LENGTH = 60 # in seconds
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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translator = Translator(
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model_name_or_card="multitask_unity_large",
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@@ -43,6 +48,9 @@ def predict(
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target_language: str,
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) -> tuple[tuple[int, np.ndarray] | None, str]:
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task_name = task_name.split()[0]
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if task_name in ["S2ST", "S2TT", "ASR"]:
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if audio_source == "microphone":
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input_data = input_audio_mic
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@@ -61,8 +69,8 @@ def predict(
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text_out, wav, sr = translator.predict(
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input=input_data,
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task_str=task_name,
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tgt_lang=
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src_lang=
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)
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if task_name in ["S2ST", "T2ST"]:
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return (sr, wav.cpu().detach().numpy()), text_out
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@@ -80,26 +88,50 @@ def update_audio_ui(audio_source: str) -> tuple[dict, dict]:
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def update_input_ui(task_name: str) -> tuple[dict, dict, dict, dict]:
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task_name = task_name.split()[0]
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if task_name
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return (
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gr.update(visible=True), # audio_box
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gr.update(visible=False), # input_text
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gr.update(visible=False), # source_language
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gr.update(
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)
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elif task_name
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return (
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gr.update(visible=False), # audio_box
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gr.update(visible=True), # input_text
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gr.update(visible=True), # source_language
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gr.update(
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)
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elif task_name == "ASR":
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return (
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gr.update(visible=True), # audio_box
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gr.update(visible=False), # input_text
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gr.update(visible=False), # source_language
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gr.update(
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)
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else:
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raise ValueError(f"Unknown task: {task_name}")
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@@ -137,14 +169,14 @@ with gr.Blocks(css="style.css") as demo:
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with gr.Row():
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source_language = gr.Dropdown(
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label="Source language",
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choices=
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value="
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visible=False,
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)
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target_language = gr.Dropdown(
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label="Target language",
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choices=
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value=
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)
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with gr.Row() as audio_box:
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audio_source = gr.Radio(
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import os
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import gradio as gr
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import torchaudio
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from seamless_communication.models.inference.translator import Translator
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from lang_list import (
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LANGUAGE_NAME_TO_CODE,
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S2ST_TARGET_LANGUAGE_NAMES,
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S2TT_TARGET_LANGUAGE_NAMES,
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T2TT_TARGET_LANGUAGE_NAMES,
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TEXT_SOURCE_LANGUAGE_NAMES,
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)
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DESCRIPTION = "# SeamlessM4T"
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TASK_NAMES = [
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"S2ST (Speech to Speech translation)",
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AUDIO_SAMPLE_RATE = 16000.0
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MAX_INPUT_AUDIO_LENGTH = 60 # in seconds
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DEFAULT_TARGET_LANGUAGE = "French"
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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translator = Translator(
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model_name_or_card="multitask_unity_large",
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target_language: str,
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) -> tuple[tuple[int, np.ndarray] | None, str]:
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task_name = task_name.split()[0]
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source_language_code = LANGUAGE_NAME_TO_CODE[source_language]
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target_language_code = LANGUAGE_NAME_TO_CODE[target_language]
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if task_name in ["S2ST", "S2TT", "ASR"]:
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if audio_source == "microphone":
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input_data = input_audio_mic
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text_out, wav, sr = translator.predict(
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input=input_data,
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task_str=task_name,
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tgt_lang=target_language_code,
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src_lang=source_language_code,
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)
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if task_name in ["S2ST", "T2ST"]:
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return (sr, wav.cpu().detach().numpy()), text_out
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def update_input_ui(task_name: str) -> tuple[dict, dict, dict, dict]:
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task_name = task_name.split()[0]
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if task_name == "S2ST":
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return (
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gr.update(visible=True), # audio_box
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gr.update(visible=False), # input_text
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gr.update(visible=False), # source_language
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gr.update(
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visible=True, choices=S2ST_TARGET_LANGUAGE_NAMES, value=DEFAULT_TARGET_LANGUAGE
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), # target_language
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)
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elif task_name == "S2TT":
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return (
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gr.update(visible=True), # audio_box
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gr.update(visible=False), # input_text
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gr.update(visible=False), # source_language
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gr.update(
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visible=True, choices=S2TT_TARGET_LANGUAGE_NAMES, value=DEFAULT_TARGET_LANGUAGE
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), # target_language
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)
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elif task_name == "T2ST":
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return (
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gr.update(visible=False), # audio_box
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gr.update(visible=True), # input_text
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gr.update(visible=True), # source_language
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gr.update(
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visible=True, choices=S2ST_TARGET_LANGUAGE_NAMES, value=DEFAULT_TARGET_LANGUAGE
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), # target_language
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)
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elif task_name == "T2TT":
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return (
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gr.update(visible=False), # audio_box
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gr.update(visible=True), # input_text
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gr.update(visible=True), # source_language
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gr.update(
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visible=True, choices=T2TT_TARGET_LANGUAGE_NAMES, value=DEFAULT_TARGET_LANGUAGE
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), # target_language
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)
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elif task_name == "ASR":
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return (
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gr.update(visible=True), # audio_box
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gr.update(visible=False), # input_text
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gr.update(visible=False), # source_language
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gr.update(
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visible=True, choices=S2TT_TARGET_LANGUAGE_NAMES, value=DEFAULT_TARGET_LANGUAGE
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), # target_language
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)
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else:
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raise ValueError(f"Unknown task: {task_name}")
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with gr.Row():
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source_language = gr.Dropdown(
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label="Source language",
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choices=TEXT_SOURCE_LANGUAGE_NAMES,
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value="English",
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visible=False,
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)
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target_language = gr.Dropdown(
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label="Target language",
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choices=S2ST_TARGET_LANGUAGE_NAMES,
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value=DEFAULT_TARGET_LANGUAGE,
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)
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with gr.Row() as audio_box:
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audio_source = gr.Radio(
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lang_list.py
ADDED
@@ -0,0 +1,254 @@
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+
# Language dict
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language_code_to_name = {
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"afr": "Afrikaans",
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"amh": "Amharic",
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"arb": "Modern Standard Arabic",
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"ary": "Moroccan Arabic",
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"arz": "Egyptian Arabic",
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"asm": "Assamese",
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"ast": "Asturian",
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"azj": "North Azerbaijani",
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"bel": "Belarusian",
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"ben": "Bengali",
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"bos": "Bosnian",
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"bul": "Bulgarian",
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"cat": "Catalan",
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"ceb": "Cebuano",
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"ces": "Czech",
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"ckb": "Central Kurdish",
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"cmn": "Mandarin Chinese",
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"cym": "Welsh",
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"dan": "Danish",
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"deu": "German",
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"ell": "Greek",
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"eng": "English",
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"est": "Estonian",
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"eus": "Basque",
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+
"fin": "Finnish",
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+
"fra": "French",
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+
"gaz": "West Central Oromo",
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+
"gle": "Irish",
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+
"glg": "Galician",
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+
"guj": "Gujarati",
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+
"heb": "Hebrew",
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+
"hin": "Hindi",
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+
"hrv": "Croatian",
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"hun": "Hungarian",
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+
"hye": "Armenian",
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+
"ibo": "Igbo",
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"ind": "Indonesian",
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+
"isl": "Icelandic",
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+
"ita": "Italian",
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"jav": "Javanese",
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+
"jpn": "Japanese",
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+
"kam": "Kamba",
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"kan": "Kannada",
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"kat": "Georgian",
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+
"kaz": "Kazakh",
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"kea": "Kabuverdianu",
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+
"khk": "Halh Mongolian",
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"khm": "Khmer",
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+
"kir": "Kyrgyz",
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+
"kor": "Korean",
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"lao": "Lao",
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"lit": "Lithuanian",
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"ltz": "Luxembourgish",
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"lug": "Ganda",
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"luo": "Luo",
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"lvs": "Standard Latvian",
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"mai": "Maithili",
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"mal": "Malayalam",
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"mar": "Marathi",
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"mkd": "Macedonian",
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+
"mlt": "Maltese",
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"mni": "Meitei",
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"mya": "Burmese",
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+
"nld": "Dutch",
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+
"nno": "Norwegian Nynorsk",
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+
"nob": "Norwegian Bokm\u00e5l",
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+
"npi": "Nepali",
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+
"nya": "Nyanja",
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+
"oci": "Occitan",
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+
"ory": "Odia",
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+
"pan": "Punjabi",
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+
"pbt": "Southern Pashto",
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+
"pes": "Western Persian",
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+
"pol": "Polish",
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+
"por": "Portuguese",
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+
"ron": "Romanian",
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+
"rus": "Russian",
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80 |
+
"slk": "Slovak",
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+
"slv": "Slovenian",
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+
"sna": "Shona",
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+
"snd": "Sindhi",
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+
"som": "Somali",
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+
"spa": "Spanish",
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+
"srp": "Serbian",
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+
"swe": "Swedish",
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+
"swh": "Swahili",
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+
"tam": "Tamil",
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+
"tel": "Telugu",
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+
"tgk": "Tajik",
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+
"tgl": "Tagalog",
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+
"tha": "Thai",
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+
"tur": "Turkish",
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+
"ukr": "Ukrainian",
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+
"urd": "Urdu",
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+
"uzn": "Northern Uzbek",
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98 |
+
"vie": "Vietnamese",
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+
"xho": "Xhosa",
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+
"yor": "Yoruba",
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+
"yue": "Cantonese",
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102 |
+
"zlm": "Colloquial Malay",
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103 |
+
"zsm": "Standard Malay",
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+
"zul": "Zulu",
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+
}
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106 |
+
LANGUAGE_NAME_TO_CODE = {v: k for k, v in language_code_to_name.items()}
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107 |
+
|
108 |
+
# Source langs: S2ST / S2TT / ASR don't need source lang
|
109 |
+
# T2TT / T2ST use this
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110 |
+
text_source_language_codes = [
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111 |
+
"afr",
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112 |
+
"amh",
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113 |
+
"arb",
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114 |
+
"ary",
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115 |
+
"arz",
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116 |
+
"asm",
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117 |
+
"azj",
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+
"bel",
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119 |
+
"ben",
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120 |
+
"bos",
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121 |
+
"bul",
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122 |
+
"cat",
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123 |
+
"ceb",
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124 |
+
"ces",
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125 |
+
"ckb",
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+
"cmn",
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127 |
+
"cym",
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128 |
+
"dan",
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129 |
+
"deu",
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130 |
+
"ell",
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131 |
+
"eng",
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132 |
+
"est",
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133 |
+
"eus",
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134 |
+
"fin",
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135 |
+
"fra",
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136 |
+
"gaz",
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137 |
+
"gle",
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138 |
+
"glg",
|
139 |
+
"guj",
|
140 |
+
"heb",
|
141 |
+
"hin",
|
142 |
+
"hrv",
|
143 |
+
"hun",
|
144 |
+
"hye",
|
145 |
+
"ibo",
|
146 |
+
"ind",
|
147 |
+
"isl",
|
148 |
+
"ita",
|
149 |
+
"jav",
|
150 |
+
"jpn",
|
151 |
+
"kan",
|
152 |
+
"kat",
|
153 |
+
"kaz",
|
154 |
+
"khk",
|
155 |
+
"khm",
|
156 |
+
"kir",
|
157 |
+
"kor",
|
158 |
+
"lao",
|
159 |
+
"lit",
|
160 |
+
"lug",
|
161 |
+
"luo",
|
162 |
+
"lvs",
|
163 |
+
"mai",
|
164 |
+
"mal",
|
165 |
+
"mar",
|
166 |
+
"mkd",
|
167 |
+
"mlt",
|
168 |
+
"mni",
|
169 |
+
"mya",
|
170 |
+
"nld",
|
171 |
+
"nno",
|
172 |
+
"nob",
|
173 |
+
"npi",
|
174 |
+
"nya",
|
175 |
+
"ory",
|
176 |
+
"pan",
|
177 |
+
"pbt",
|
178 |
+
"pes",
|
179 |
+
"pol",
|
180 |
+
"por",
|
181 |
+
"ron",
|
182 |
+
"rus",
|
183 |
+
"slk",
|
184 |
+
"slv",
|
185 |
+
"sna",
|
186 |
+
"snd",
|
187 |
+
"som",
|
188 |
+
"spa",
|
189 |
+
"srp",
|
190 |
+
"swe",
|
191 |
+
"swh",
|
192 |
+
"tam",
|
193 |
+
"tel",
|
194 |
+
"tgk",
|
195 |
+
"tgl",
|
196 |
+
"tha",
|
197 |
+
"tur",
|
198 |
+
"ukr",
|
199 |
+
"urd",
|
200 |
+
"uzn",
|
201 |
+
"vie",
|
202 |
+
"yor",
|
203 |
+
"yue",
|
204 |
+
"zsm",
|
205 |
+
"zul",
|
206 |
+
]
|
207 |
+
TEXT_SOURCE_LANGUAGE_NAMES = sorted([language_code_to_name[code] for code in text_source_language_codes])
|
208 |
+
|
209 |
+
# Target langs:
|
210 |
+
# S2ST / T2ST
|
211 |
+
s2st_target_language_codes = [
|
212 |
+
"eng",
|
213 |
+
"arb",
|
214 |
+
"ben",
|
215 |
+
"cat",
|
216 |
+
"ces",
|
217 |
+
"cmn",
|
218 |
+
"cym",
|
219 |
+
"dan",
|
220 |
+
"deu",
|
221 |
+
"est",
|
222 |
+
"fin",
|
223 |
+
"fra",
|
224 |
+
"hin",
|
225 |
+
"ind",
|
226 |
+
"ita",
|
227 |
+
"jpn",
|
228 |
+
"kor",
|
229 |
+
"mlt",
|
230 |
+
"nld",
|
231 |
+
"pes",
|
232 |
+
"pol",
|
233 |
+
"por",
|
234 |
+
"ron",
|
235 |
+
"rus",
|
236 |
+
"slk",
|
237 |
+
"spa",
|
238 |
+
"swe",
|
239 |
+
"swh",
|
240 |
+
"tel",
|
241 |
+
"tgl",
|
242 |
+
"tha",
|
243 |
+
"tur",
|
244 |
+
"ukr",
|
245 |
+
"urd",
|
246 |
+
"uzn",
|
247 |
+
"vie",
|
248 |
+
]
|
249 |
+
S2ST_TARGET_LANGUAGE_NAMES = sorted([language_code_to_name[code] for code in s2st_target_language_codes])
|
250 |
+
|
251 |
+
# S2TT / ASR
|
252 |
+
S2TT_TARGET_LANGUAGE_NAMES = TEXT_SOURCE_LANGUAGE_NAMES
|
253 |
+
# T2TT
|
254 |
+
T2TT_TARGET_LANGUAGE_NAMES = TEXT_SOURCE_LANGUAGE_NAMES
|
mlg_config.json
DELETED
@@ -1,186 +0,0 @@
|
|
1 |
-
{
|
2 |
-
"multilingual": {
|
3 |
-
"arb": 0,
|
4 |
-
"ben": 1,
|
5 |
-
"cat": 2,
|
6 |
-
"ces": 3,
|
7 |
-
"cmn": 4,
|
8 |
-
"cym": 5,
|
9 |
-
"dan": 6,
|
10 |
-
"deu": 7,
|
11 |
-
"eng": 8,
|
12 |
-
"est": 9,
|
13 |
-
"fin": 10,
|
14 |
-
"fra": 11,
|
15 |
-
"hin": 12,
|
16 |
-
"ind": 13,
|
17 |
-
"ita": 14,
|
18 |
-
"jpn": 15,
|
19 |
-
"kor": 16,
|
20 |
-
"mlt": 17,
|
21 |
-
"nld": 18,
|
22 |
-
"pes": 19,
|
23 |
-
"pol": 20,
|
24 |
-
"por": 21,
|
25 |
-
"ron": 22,
|
26 |
-
"rus": 23,
|
27 |
-
"slk": 24,
|
28 |
-
"spa": 25,
|
29 |
-
"swe": 26,
|
30 |
-
"swh": 27,
|
31 |
-
"tel": 28,
|
32 |
-
"tgl": 29,
|
33 |
-
"tha": 30,
|
34 |
-
"tur": 31,
|
35 |
-
"ukr": 32,
|
36 |
-
"urd": 33,
|
37 |
-
"uzn": 34,
|
38 |
-
"vie": 35
|
39 |
-
},
|
40 |
-
"multispkr": {
|
41 |
-
"arb": [
|
42 |
-
0
|
43 |
-
],
|
44 |
-
"ben": [
|
45 |
-
2,
|
46 |
-
1
|
47 |
-
],
|
48 |
-
"cat": [
|
49 |
-
3
|
50 |
-
],
|
51 |
-
"ces": [
|
52 |
-
4
|
53 |
-
],
|
54 |
-
"cmn": [
|
55 |
-
5
|
56 |
-
],
|
57 |
-
"cym": [
|
58 |
-
6
|
59 |
-
],
|
60 |
-
"dan": [
|
61 |
-
7,
|
62 |
-
8
|
63 |
-
],
|
64 |
-
"deu": [
|
65 |
-
9
|
66 |
-
],
|
67 |
-
"eng": [
|
68 |
-
10
|
69 |
-
],
|
70 |
-
"est": [
|
71 |
-
11,
|
72 |
-
12,
|
73 |
-
13
|
74 |
-
],
|
75 |
-
"fin": [
|
76 |
-
14
|
77 |
-
],
|
78 |
-
"fra": [
|
79 |
-
15
|
80 |
-
],
|
81 |
-
"hin": [
|
82 |
-
16
|
83 |
-
],
|
84 |
-
"ind": [
|
85 |
-
17,
|
86 |
-
24,
|
87 |
-
18,
|
88 |
-
20,
|
89 |
-
19,
|
90 |
-
21,
|
91 |
-
23,
|
92 |
-
27,
|
93 |
-
26,
|
94 |
-
22,
|
95 |
-
25
|
96 |
-
],
|
97 |
-
"ita": [
|
98 |
-
29,
|
99 |
-
28
|
100 |
-
],
|
101 |
-
"jpn": [
|
102 |
-
30
|
103 |
-
],
|
104 |
-
"kor": [
|
105 |
-
31
|
106 |
-
],
|
107 |
-
"mlt": [
|
108 |
-
32,
|
109 |
-
33,
|
110 |
-
34
|
111 |
-
],
|
112 |
-
"nld": [
|
113 |
-
35
|
114 |
-
],
|
115 |
-
"pes": [
|
116 |
-
36
|
117 |
-
],
|
118 |
-
"pol": [
|
119 |
-
37
|
120 |
-
],
|
121 |
-
"por": [
|
122 |
-
38
|
123 |
-
],
|
124 |
-
"ron": [
|
125 |
-
39
|
126 |
-
],
|
127 |
-
"rus": [
|
128 |
-
40
|
129 |
-
],
|
130 |
-
"slk": [
|
131 |
-
41
|
132 |
-
],
|
133 |
-
"spa": [
|
134 |
-
42
|
135 |
-
],
|
136 |
-
"swe": [
|
137 |
-
43,
|
138 |
-
45,
|
139 |
-
44
|
140 |
-
],
|
141 |
-
"swh": [
|
142 |
-
46,
|
143 |
-
48,
|
144 |
-
47
|
145 |
-
],
|
146 |
-
"tel": [
|
147 |
-
49
|
148 |
-
],
|
149 |
-
"tgl": [
|
150 |
-
50
|
151 |
-
],
|
152 |
-
"tha": [
|
153 |
-
51,
|
154 |
-
54,
|
155 |
-
55,
|
156 |
-
52,
|
157 |
-
53
|
158 |
-
],
|
159 |
-
"tur": [
|
160 |
-
58,
|
161 |
-
57,
|
162 |
-
56
|
163 |
-
],
|
164 |
-
"ukr": [
|
165 |
-
59
|
166 |
-
],
|
167 |
-
"urd": [
|
168 |
-
60,
|
169 |
-
61,
|
170 |
-
62
|
171 |
-
],
|
172 |
-
"uzn": [
|
173 |
-
63,
|
174 |
-
64,
|
175 |
-
65
|
176 |
-
],
|
177 |
-
"vie": [
|
178 |
-
66,
|
179 |
-
67,
|
180 |
-
70,
|
181 |
-
71,
|
182 |
-
68,
|
183 |
-
69
|
184 |
-
]
|
185 |
-
}
|
186 |
-
}
|
|
|
|
|
|
|
|
|
|
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|
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