kotoba-whisper-bilingual

faster-whisper weight, whisper.cpp weight

Kotoba-Whisper-Bilingual is a collection of distilled Whisper models trained for

• Japanese ASR
• English ASR
• Speech-to-text translation (Japanese -> English)
• Speech-to-text translation (English -> Japanese)

developed through the collaboration bewteen Asahi Ushio and Kotoba Technologies. Following the original work of distil-whisper (Robust Knowledge Distillation via Large-Scale Pseudo Labelling), we employ OpenAI's Whisper large-v3 as the teacher model for Japanese and English ASR, while we translate the transcription into English and Japanese by external LLM to obtain training dataset for speech-to-text translation. We employ ReazonSpeech for Japanese ASR and Japanese speech to English text translation, and Multilingual LibriSpeech for English ASR and English speech to Japanese text translation. Kotoba-whisper-bilingual's loss objective consists of cross-entropy on both of ASR and translation tasks, while KL divergence loss only for ASR task. The student model consists the full encoder of the teacher large-v3 model and the decoder with two layers initialized from the first and last layer of the large-v3 model.

As kotoba-whisper uses the same architecture as distil-whisper/distil-large-v3, it inherits the benefit of the improved latency compared to openai/whisper-large-v3 (6.3x faster than large-v3, see the table below taken from distil-whisper/distil-large-v3).

Evaluation

We compare our kotoba-whisper-bilingual with OpenAI whisper models, kotoba-whisper models, and cascaded models for translation. Worth noting that kotoba-whisper-bilingual is the only model that can do Japanese and English ASR and speech-to-text translation between Japanese and English, as OpenAI whisper is not trained for English to Japanese speech-to-text translation, and other models are specific to the Task (eg. kotoba-whisper is Japanese ASR and distil whisper is English ASR only).

Speech2Text Translation (Japanese->English): WER (smaller is better)