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Audio AI Researcher & Developer
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Module 10
Audio Language Models and S2S Translation
1
Neural Audio Codec Discretization
Explain how neural audio codecs like SoundStream or EnCodec discretize audio waveforms into a sequence of tokens.
2
AudioLM: Generating Audio from Discrete Tokens
Describe how a standard language model architecture (e.g., decoder-only Transformer) can be applied to discrete audio tokens for generation (AudioLM).
3
In-Context Learning in VALL-E for Audio Generation
Explain the mechanics of in-context learning for audio generation in models like VALL-E.
4
Cascaded vs. End-to-End S2ST: Trade-offs
Describe cascaded vs. end-to-end systems for Speech-to-Speech Translation (S2ST) and analyze their trade-offs.
5
Understanding Direct S2ST Model Architecture
Explain the architecture of a direct S2ST model, such as Meta's SeamlessM4T.
6
Speech-to-Speech Translation with Fairseq/ESPnet-ST
Run a speech-to-speech translation task using a pre-built recipe from a toolkit like Fairseq or ESPnet-ST.
7
Audio-Text LLM Architecture: AudioPaLM Case Study
Describe the architecture of multimodal audio-text LLMs like AudioPaLM.
8
Challenges and Future Directions in Audio Language Modeling
Discuss the challenges and future directions in audio language modeling, including long-form generation and expressiveness.
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Advanced TTS and Voice Cloning
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Model Optimization for Deployment