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--- |
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task_categories: |
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- automatic-speech-recognition |
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language: |
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- ms |
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- en |
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- zh |
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- ta |
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- id |
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--- |
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# Malaysian STT Whisper format |
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Up to 15k hours annotated, we done heavy postprocessing and post-translation to improve pseudolabeled Whisper Large V3. |
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Also include word level timestamp. |
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## Postprocessing |
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1. Check repetitive trigrams. |
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2. Verify Voice Activity using Silero-VAD. |
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3. Verify scores using Force Alignment. |
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## Post-translation |
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We use [mesolitica/nanot5-base-malaysian-translation-v2.1](https://huggingface.co/mesolitica/nanot5-base-malaysian-translation-v2.1). |
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## Dataset involved |
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1. [Malaysian context v1](https://huggingface.co/datasets/mesolitica/pseudolabel-malaya-speech-stt-train-whisper-large-v3-timestamp) |
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2. [Malaysian context v2](https://huggingface.co/datasets/mesolitica/pseudolabel-malaysian-youtube-whisper-large-v3-timestamp) |
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3. [Malay audiobook](https://huggingface.co/datasets/mesolitica/pseudolabel-nusantara-large-v3-timestamp) |
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4. [Singaporean context](https://huggingface.co/datasets/mesolitica/pseudolabel-imda-large-v3-timestamp) |
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5. [Indonesian context](https://huggingface.co/datasets/mesolitica/pseudolabel-indonesian-large-v3-timestamp) |
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6. [Mandarin audio](https://huggingface.co/datasets/mesolitica/pseudolabel-mandarin-large-v3-timestamp) |
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7. [Tamil audio](https://huggingface.co/datasets/mesolitica/pseudolabel-tamil-large-v3-timestamp) |
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8. [Science context](https://huggingface.co/datasets/mesolitica/pseudolabel-science-large-v3-timestamp) |
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9. [Malay sarawak](https://huggingface.co/datasets/malaysia-ai/sarawakmalay-whisper-format) |
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10. [Scripted Malay Daily Use Speech Corpus](https://huggingface.co/datasets/malaysia-ai/scripted-malay-daily-use-speech-corpus-whisper-format) |
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11. [Malay Conversational Speech Corpus](https://huggingface.co/datasets/malaysia-ai/malay-conversational-speech-corpus-whisper-format) |
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12. [Iban](https://huggingface.co/datasets/malaysia-ai/iban-whisper-format) |
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13. [Malay dialects](https://huggingface.co/datasets/mesolitica/pseudolabel-malay-dialects-large-v3-timestamp) |
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### Word level timestamp |
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1. Malaysian context v1, 658.54 hours. |
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``` |
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{"audio_filename": "prepared-pseudolabel-malaya-chunks/2-0.mp3", "new_text": "<|startoftranscript|><|ms|><|transcribeprecise|><|0.00|> luar<|0.34|><|0.42|> kan<|0.60|><|1.78|> sebab<|2.06|><|2.24|> benda<|2.42|><|2.52|> ni<|2.58|><|2.70|> berlaku<|3.08|><|3.20|> contoh<|3.50|><|3.56|> kita<|3.72|><|3.80|> pergi<|3.98|><|4.10|> ke<|4.16|><|4.40|> ATM<|4.76|><|5.70|> yang<|5.80|><|5.84|> bukan<|6.02|><|6.10|> Islam,<|6.34|><|6.96|> siang<|7.12|><|7.18|> hari<|7.42|><|endoftext|>"} |
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``` |
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- [Label](pseudolabel-malaya-whisper-word-timestamp.jsonl) |
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- [Audio](prepared-pseudolabel-malaya-chunks.zip) |
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2. Malaysian context v2, 8058.17 hours. |
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``` |
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{"audio_filename": "prepared-pseudolabel-chunks/0-0.mp3", "new_text": "<|startoftranscript|><|ms|><|transcribeprecise|><|0.00|> tu<|0.04|><|0.20|> So<|0.26|><|0.70|> gaji<|0.96|><|1.06|> berbeza<|1.42|><|2.46|> Gaji<|2.86|><|endoftext|>"} |
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``` |
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- [Label](pseudolabel-whisper-word-timestamp.jsonl) |
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- [Audio](prepared-pseudolabel_alignment) |
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3. Singaporean context, 1829.21 hours. |
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``` |
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{"audio_filename": "prepared-imda-chunks/0-0.mp3", "new_text": "<|startoftranscript|><|en|><|transcribeprecise|><|0.00|> Households<|0.58|><|0.64|> with<|0.76|><|0.86|> target<|1.16|><|1.24|> sets<|1.50|><|1.70|> were<|1.82|><|1.90|> encouraged<|2.40|><|2.44|> to<|2.48|><|2.62|> try<|2.80|><|2.90|> keeping<|3.24|><|endoftext|>"} |
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``` |
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- [Label](imda-whisper-word-timestamp.jsonl) |
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- [Audio](prepared-imda_alignment) |
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4. Science context, 4992.42 hours. |
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``` |
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{"audio_filename": "prepared-science-chunks/0-0.mp3", "new_text": "<|startoftranscript|><|en|><|transcribeprecise|><|0.00|> Visual<|0.24|><|0.30|> Studio<|0.60|><|0.76|> Code<|1.00|><|1.06|> integration.<|1.68|><|3.46|> Here's<|3.70|><|3.76|> what<|3.88|><|3.94|> will<|4.06|><|4.10|> be<|4.14|><|4.28|> new.<|4.44|><|5.36|> You<|5.42|><|5.46|> will<|5.58|><|5.62|> have<|5.74|><|5.82|> more<|5.96|><|6.08|> choice<|6.40|><|6.48|> on<|6.52|><|6.60|> runtime<|6.96|><|7.02|> experiences.<|7.82|><|8.78|> Java<|9.06|><|9.16|> interoperability<|10.04|><|10.22|> will<|10.32|><|10.36|> be<|10.40|><|10.48|> available<|10.90|><|10.96|> on<|11.00|><|11.08|> all<|11.14|><|11.22|> platforms.<|11.78|><|12.22|> Objective<|12.68|><|12.78|> C<|12.78|><|13.00|> and<|13.06|><|13.16|> Swift<|13.42|><|13.48|> interoperability<|14.38|><|14.92|> will<|15.04|><|15.08|> be<|15.12|><|15.26|> supported<|15.70|><|15.78|> on<|15.82|><|15.90|> multiple<|16.26|><|16.34|> operating<|16.78|><|16.86|> systems.<|17.28|><|18.28|> Core<|18.62|><|18.74|> FX<|18.98|><|19.20|> will<|19.30|><|19.34|> be<|19.38|><|19.46|> extended<|19.96|><|20.30|> to<|20.34|><|20.42|> support<|20.74|><|20.84|> static<|21.16|><|21.22|> compilation<|22.04|><|endoftext|>"} |
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``` |
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- [Label](prepared-science-word-timestamp.jsonl) |
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- [Audio](prepared-science_alignment) |
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## how to prepare the dataset |
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```bash |
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wget https://www.7-zip.org/a/7z2301-linux-x64.tar.xz |
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tar -xf 7z2301-linux-x64.tar.xz |
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# Malaysian context |
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wget https://huggingface.co/datasets/mesolitica/Malaysian-STT-Whisper/resolve/main/malaysian-stt.jsonl |
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huggingface-cli download --repo-type dataset \ |
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--include 'output-audio-malaya.z*' \ |
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--local-dir './' \ |
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mesolitica/pseudolabel-malaya-speech-stt-train-whisper-large-v3-timestamp |
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./7zz x output-audio-malaya.zip -y -mmt40 |
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huggingface-cli download --repo-type dataset \ |
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--include 'output-audio.z*' \ |
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--local-dir './' \ |
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mesolitica/pseudolabel-malaysian-youtube-whisper-large-v3-timestamp |
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./7zz x output-audio.zip -y -mmt40 |
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# Malay audiobook |
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wget https://huggingface.co/datasets/mesolitica/pseudolabel-nusantara-large-v3-timestamp/resolve/main/split-nusantara.zip |
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wget https://huggingface.co/datasets/mesolitica/pseudolabel-nusantara-large-v3-timestamp/resolve/main/prepared-nusantara.jsonl |
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unzip split-nusantara.zip |
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# Singaporean context |
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wget https://huggingface.co/datasets/mesolitica/pseudolabel-imda-large-v3-timestamp/resolve/main/prepared-imda.jsonl |
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wget https://huggingface.co/datasets/mesolitica/pseudolabel-imda-large-v3-timestamp/resolve/main/prepared-imda-ms.jsonl |
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huggingface-cli download --repo-type dataset \ |
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--include '*.7z*' \ |
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--local-dir './' \ |
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mesolitica/IMDA-STT |
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./7zz x part1-mp3.7z.001 -y -mmt40 |
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./7zz x part2-mp3.7z.001 -y -mmt40 |
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./7zz x part3-same-audio-mp3.7z.001 -y -mmt40 |
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./7zz x part3-separate-audio-mp3.7z.001 -y -mmt40 |
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./7zz x part4-same-audio-mp3.7z.001 -y -mmt40 |
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./7zz x part4-separate-audio-mp3.7z.001 -y -mmt40 |
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./7zz x part5-same-audio-mp3.7z.001 -y -mmt40 |
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./7zz x part5-separate-audio-mp3.7z.001 -y -mmt40 |
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./7zz x part6-1-audio-mp3.7z.001 -y -mmt40 |
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./7zz x part6-2-audio-mp3.7z.001 -y -mmt40 |
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./7zz x part6-3-audio-mp3.7z.001 -y -mmt40 |
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# Indonesian context |
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huggingface-cli download --repo-type dataset \ |
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--include 'split-indonesian.z*' \ |
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--local-dir './' \ |
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mesolitica/pseudolabel-indonesian-large-v3-timestamp |
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./7zz x split-indonesian.zip -y -mmt40 |
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# Science context |
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wget https://huggingface.co/datasets/mesolitica/Malaysian-STT-Whisper/resolve/main/science-en-stt.jsonl |
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wget https://huggingface.co/datasets/mesolitica/Malaysian-STT-Whisper/resolve/main/science-ms-stt.jsonl |
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huggingface-cli download --repo-type dataset \ |
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--include 'audio-chunk.z*' \ |
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--local-dir './' \ |
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mesolitica/pseudolabel-science-large-v3-timestamp |
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./7zz x audio-chunk.zip -y -mmt40 |
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# Malay sarawak |
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wget https://huggingface.co/datasets/malaysia-ai/sarawakmalay-whisper-format/resolve/main/sarawakmalay.zip |
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wget https://huggingface.co/datasets/malaysia-ai/sarawakmalay-whisper-format/resolve/main/dataset.json -O sarawakmalay.json |
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unzip sarawakmalay.zip |
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# for Scripted Malay Daily Use Speech Corpus |
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wget https://huggingface.co/datasets/malaysia-ai/scripted-malay-daily-use-speech-corpus-whisper-format/resolve/main/scripted-malay-daily-use-speech-corpus-whisper-format.zip |
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wget https://huggingface.co/datasets/malaysia-ai/scripted-malay-daily-use-speech-corpus-whisper-format/resolve/main/scripted-malay-daily-use-speech-corpus-whisper-format.json |
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unzip scripted-malay-daily-use-speech-corpus-whisper-format.zip |
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# Malay Conversational Speech Corpus |
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wget https://huggingface.co/datasets/malaysia-ai/malay-conversational-speech-corpus-whisper-format/resolve/main/malay-conversational-speech-corpus-whisper-format.zip |
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wget https://huggingface.co/datasets/malaysia-ai/malay-conversational-speech-corpus-whisper-format/resolve/main/malay-conversational-speech-corpus-whisper-format.json |
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unzip malay-conversational-speech-corpus-whisper-format.zip |
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# Iban |
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wget https://huggingface.co/datasets/malaysia-ai/iban-whisper-format/resolve/main/iban-wav.zip |
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wget https://huggingface.co/datasets/malaysia-ai/iban-whisper-format/resolve/main/iban-dataset.json |
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unzip iban-wav.zip |
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``` |
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## Source code |
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Source code at https://github.com/mesolitica/malaysian-dataset/tree/master/speech-to-text-semisupervised/distilled-malaysian-whisper |