A curated 18-month learning roadmap for becoming an AI Speech Engineer — covering foundations, core technologies (ASR, TTS, Speaker Verification, Diarization, Voice Conversion), …
Speaker Diarization answers "Who spoken when?" — covering core concepts, traditional and modern end-to-end approaches, and the latest Sortformer model for speaker segmentation.
Understanding entropy and why it's a core concept in decision trees, neural networks, and loss functions like cross-entropy.
Exploring LoRA-Whisper, a scalable and efficient approach for multilingual ASR using Low-Rank Adaptation to fine-tune OpenAI's Whisper model while avoiding catastrophic forgetting …
Overview This thesis develops a voice conversion model for Vietnamese based on the Phoneme Hallucinator model with 2 adoptions: (1) Add a Text2SSL module to get more context …
Generally speaking, the postnet layer receives a mel-spectrogram and predicts another mel-spectrogram with additional information. That makes the output mel-spectrogram more …