A system and method for converting a chinese dialect phonetic transcription into international phonetic alphabet transcription
By employing a self-supervised pre-trained acoustic model and a small-sample fine-tuning mechanism with a configurable IPA syllable list, the problem of resource scarcity in Chinese dialect speech recognition is solved, enabling efficient and accurate transcription of Chinese dialect speech with limited data, thus improving the adaptability and accuracy of the recognition system.
CN122454958APending Publication Date: 2026-07-24HANGZHOU NORMAL UNIVERSITY
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Patent Information
- Application Number
- CN202610826979.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-06-09
- Publication Date
- 2026-07-24
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Figure CN122454958A_ABST
Abstract
The application discloses a Chinese dialect phonetic international phonetic alphabet transcription method and system. The application comprises: 1. A pre-trained self-supervised acoustic model is used as a feature extractor to convert the input dialect audio into implicit speech representation; 2. A configurable IPA syllable list of dialects is constructed: a configuration mechanism of the IPA syllable list required by the target dialect is provided according to the requirement; 3. The acoustic model is retrained through a small sample fine-tuning mechanism: the dialect corpus within a specified time is labeled, and the labeled target dialect corpus is used to continue training part of the parameters of the acoustic model to complete fine-tuning adaptation, so that the model can better capture the acoustic characteristics of the target dialect; 4. The frame-by-frame syllable output by the small sample fine-tuned acoustic model is mapped into the final IPA syllable sequence by using an IPA decoding module. The application can realize accurate transcription of dialect phonetics under a small amount of labeled corpus, and solve the technical problem of standardized phonetic transcription caused by the lack of large-scale training data of Chinese dialects.
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