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README.md
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"TalTechNLP/espnet2_estonian"
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speech, rate = soundfile.read("speech.wav")
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text, *_ = model(speech)
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```
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#### Limitations and bias
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## Training data
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## Training procedure
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## Evaluation results
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### BibTeX entry and citation info
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"TalTechNLP/espnet2_estonian"
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)
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# read a sound file with 16k sample rate
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import soundfile
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speech, rate = soundfile.read("speech.wav")
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assert rate == 16000
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text, *_ = model(speech)
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print(text[0])
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```
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#### Limitations and bias
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## Training data
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Acoustic training data:
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| Type | Amount |
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|-----------------------|:------:|
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| Broadcast speech | 591 |
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| Spontaneous speech | 53 |
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| Elderly speech corpus | 53 |
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| Talks, lectures | 49 |
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| Parliament speeches | 31 |
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| *Total* | *761* |
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Language model training data:
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* Estonian National Corpus 2019
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* OpenSubtitles
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* Speech transcripts
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## Training procedure
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Standard EspNet2 Conformer recipe.
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## Evaluation results
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### WER
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|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
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|---|---|---|---|---|---|---|---|---|
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|decode_asr_lm_lm_large_valid.loss.ave_5best_asr_model_valid.acc.ave/aktuaalne2021.testset|2864|56575|93.1|4.5|2.4|2.0|8.9|63.4|
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|decode_asr_lm_lm_large_valid.loss.ave_5best_asr_model_valid.acc.ave/jutusaated.devset|273|4677|93.9|3.6|2.4|1.2|7.3|46.5|
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|decode_asr_lm_lm_large_valid.loss.ave_5best_asr_model_valid.acc.ave/jutusaated.testset|818|11093|94.7|2.7|2.5|0.9|6.2|45.0|
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|decode_asr_lm_lm_large_valid.loss.ave_5best_asr_model_valid.acc.ave/www-trans.devset|1207|13865|82.3|8.5|9.3|3.4|21.2|74.1|
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|decode_asr_lm_lm_large_valid.loss.ave_5best_asr_model_valid.acc.ave/www-trans.testset|1648|22707|86.4|7.6|6.0|2.5|16.1|75.7|
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### BibTeX entry and citation info
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