Automated Production Program for Emotional Phonics Teaching Materials
Utilizing Kimi-Audio's TTS+SER combination function, this can be achieved by the following process:
- text markup: Insertion in the original textbook
[happy]and other sentiment tags, XML format is recommended:<segment emotion="happy">今天真是美好的一天!</segment> - Batch Speech Synthesis: Use
KimiAudioBatchClass handles markup text, key parameters:tts_params = {"emotion_embedding":True, "speaker_idx":2} - Closed Loop Quality Verification: Send the generated audio back to the SER module to verify the sentiment match, set the threshold > 0.85 to pass
Advanced programs can build audio pipelines:
1) Text Preprocessing → 2) Emotion TTS Generation → 3) SEC Scene Classification → 4) SER Quality Check → 5) AAC Subtitle Generation. It is recommended to use Docker-Compose to deploy microservices for each module and realize task scheduling through Redis queues.
This answer comes from the articleKimi-Audio: Open Source Audio Processing and Dialogue Base ModelingThe
May not be reproduced without permission:AI productivity tools " How to realize automatic generation of speech materials with emotion annotation in educational applications?
