Datasets:
Modalities:
Audio
Sub-tasks:
speaker-identification
Languages:
Japanese
Size:
100K<n<1M
Tags:
speech-recognition
License:
add main files
Browse files- README.md +52 -1
- chsakura_asr.py +12 -0
- dataset_infos.json +65 -0
- retriever.sh +26 -0
README.md
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---
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-
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---
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---
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pretty_name: banksakura
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annotations_creators:
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- expert-generated
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language_creators:
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- crowdsourced
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- expert-generated
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language:
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- ja
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license:
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- cc
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multilinguality:
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- monolingual
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size_categories:
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- 100K<n<1M
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source_datasets:
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- found
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task_categories:
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- automatic-speech-recognition
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- audio-classification
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task_ids:
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- automatic-speech-recognition
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- speech-recognition
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- speaker-identification
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---
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# CABank Japanese CallHome Corpus
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- Participants: 120
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- Type of Study: phone call
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- Location: United States
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- Media type: audio
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- DOI: doi:10.21415/T5H59V
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- Web: https://ca.talkbank.org/access/CallHome/jpn.html
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## Citation information
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Some citation here.
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In accordance with TalkBank rules, any use of data from this corpus must be accompanied by at least one of the above references.
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## Project Description
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This is the Japanese portion of CallHome.
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Speakers were solicited by the LDC to participate in this telephone speech collection effort via the internet, publications (advertisements), and personal contacts. A total of 200 call originators were found, each of whom placed a telephone call via a toll-free robot operator maintained by the LDC. Access to the robot operator was possible via a unique Personal Identification Number (PIN) issued by the recruiting staff at the LDC when the caller enrolled in the project. The participants were made aware that their telephone call would be recorded, as were the call recipients. The call was allowed only if both parties agreed to being recorded. Each caller was allowed to talk up to 30 minutes. Upon successful completion of the call, the caller was paid $20 (in addition to making a free long-distance telephone call). Each caller was allowed to place only one telephone call.
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Although the goal of the call collection effort was to have unique speakers in all calls, a handful of repeat speakers are included in the corpus. In all, 200 calls were transcribed. Of these, 80 have been designated as training calls, 20 as development test calls, and 100 as evaluation test calls. For each of the training and development test calls, a contiguous 10-minute region was selected for transcription; for the evaluation test calls, a 5-minute region was transcribed. For the present publication, only 20 of the evaluation test calls are being released; the remaining 80 test calls are being held in reserve for future LVCSR benchmark tests.
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After a successful call was completed, a human audit of each telephone call was conducted to verify that the proper language was spoken, to check the quality of the recording, and to select and describe the region to be transcribed. The description of the transcribed region provides information about channel quality, number of speakers, their gender, and other attributes.
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## Acknowledgements
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Andrew Yankes reformatted this corpus into accord with current versions of CHAT.
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chsakura_asr.py
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# coding=utf-8
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# Copyright 2022 CC - Fhrozen (Hitachi LTD.).
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#
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# Lint as: python3
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"""Librispeech automatic speech recognition dataset."""
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import os
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import datasets
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from datasets.tasks import AutomaticSpeechRecognition
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dataset_infos.json
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{
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"test": {
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"description": "Speakers were solicited by the LDC to participate in this telephone speech collection effort via the internet, publications (advertisements), and personal contacts\n",
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"citation": null,
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"homepage": "https://ca.talkbank.org/access/CallHome/jpn.html",
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"license": "",
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"features": {
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"file": {
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"dtype": "string",
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"id": null,
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"_type": "Value"
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},
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"audio": {
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"sampling_rate": 16000,
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"mono": true,
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"decode": true,
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"id": null,
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"_type": "Audio"
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},
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"text": {
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"dtype": "string",
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"id": null,
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"_type": "Value"
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},
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"speaker_id": {
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"dtype": "int64",
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"id": null,
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"_type": "Value"
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},
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"chapter_id": {
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"dtype": "int64",
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"id": null,
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"_type": "Value"
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},
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"id": {
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"dtype": "string",
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"id": null,
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"_type": "Value"
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}
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},
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"post_processed": null,
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"supervised_keys": {
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"input": "file",
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"output": "text"
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},
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"task_templates": [{
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"task": "automatic-speech-recognition",
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"audio_column": "audio",
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"transcription_column": "text"
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}],
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"builder_name": "chsakura_asr",
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"config_name": "clean",
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"version": {
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"version_str": "0.1.0",
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"description": "",
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"major": 0,
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"minor": 1,
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"patch": 0
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},
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"download_size": null,
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"post_processing_size": null,
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"dataset_size": null,
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"size_in_bytes": null
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}
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}
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retriever.sh
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#!/usr/bin/env bash
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set -e
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set -u
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set -o pipefail
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lang="jpn"
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main_link="https://media.talkbank.org/ca/CallHome/${lang}/0wav/"
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rm -f *.txt
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wget --no-check-certificate ${main_link} -O orig_lnk.txt
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ext=wav
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mkdir -p dummy/${ext}
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grep -e '.'"${ext}"'"' orig_lnk.txt | sed -e 's|.*href="||g' \
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| sed -e 's|">.*||g' \
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| awk -v LNK=${main_link} '{print LNK "/" $1}' > ${ext}_links.txt
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wget --no-check-certificate -i ${ext}_links.txt -c -nc -t 3 -P dummy/${ext}
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wget --no-check-certificate https://ca.talkbank.org/data/CallHome/${lang}.zip -c -nc -t 3
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unzip -q ${lang}.zip
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mv ${lang} dummy/cha
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rm -f *.txt
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