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--- |
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license: apache-2.0 |
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widget: |
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- example_title: Нейронные сети - это хорошо! |
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src: >- |
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https://huggingface.co/bond005/whisper-large-v2-ru-podlodka/resolve/main/test_sound_ru.flac |
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- example_title: >- |
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К сожалению, система распознавания речи не всегда стабильна, особенно в |
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шумных условиях. |
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src: >- |
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https://huggingface.co/bond005/whisper-large-v2-ru-podlodka/resolve/main/test_sound_with_noise.wav |
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- example_title: >- |
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Мимо театра мальчик ходил довольно часто — белое, со взбитыми сливками, |
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здание-торт. |
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src: >- |
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https://huggingface.co/bond005/whisper-large-v2-ru-podlodka/resolve/main/anna_matveeva_test.wav |
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datasets: |
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- bond005/taiga_speech_v2 |
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- bond005/podlodka_speech |
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- bond005/rulibrispeech |
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language: |
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- ru |
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pipeline_tag: automatic-speech-recognition |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Large V2 Russian Podlodka by Ivan Bondarenko |
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results: |
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- task: |
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name: Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Podlodka.io |
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type: bond005/podlodka_speech |
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args: ru |
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metrics: |
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- name: WER (with punctuation and capital letters) |
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type: wer |
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value: 17.4103 |
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- task: |
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name: Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Podlodka.io |
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type: bond005/podlodka_speech |
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args: ru |
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metrics: |
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- name: WER (without punctuation) |
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type: wer |
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value: 9.0987 |
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- task: |
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name: Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Russian Librispeech |
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type: bond005/rulibrispeech |
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args: ru |
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metrics: |
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- name: WER (without punctuation) |
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type: wer |
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value: 20.961 |
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--- |
