Background and Pain Points
In multinational organizations or multilingual teams, meeting recordings often involve different Asian languages or dialects. Traditional methods require manual separation of audio and switching between different language models, which is time-consuming, labor-intensive and prone to errors.
Dolphin Solutions
- Automatic Language RecognitionAutomatic detection of 40 Asian languages and 22 dialects through the LID function, without the need to pre-specify the language type.
- Batch Processing Configuration: Command line mode is available with
--lang_sym autoParameters for automatic multi-language switching recognition - segmentation optimization::
- Split the long audio with the VAD function first
dolphin meeting.wav --vad true
- Performs multi-language recognition of segmented audio batches.
for segment in *.wav; do dolphin $segment --lang_sym auto; done
- Split the long audio with the VAD function first
advanced skill
For mixed language scenarios, it can be paired with FFmpeg preprocessing:ffmpeg -i input.mp3 -ac 1 -ar 16000 -c:a pcm_s16le output.wav
Ensure that the audio sample rate is adapted to the model requirements to improve recognition accuracy.
This answer comes from the articleDolphin: Asian Language Recognition and Speech-to-Text Modeling for Asian LanguagesThe
May not be reproduced without permission:AI productivity tools " How to solve the problem of inefficient transcription of multilingual conference recordings?
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