google_speech_command_xvector

By training on more than 630 k audio‑text pairs from the LAION‑Audio‑630K dataset, it can map any audio clip to a dense vector that aligns with the vector of its textual caption.

MuQ‑large‑msd‑iter is a large‑scale music foundation model released by OpenMuQ .

It is built on the ECAPA‑TDNN architecture, originally designed for speaker recognition, and adapts it for language classification by adding fully‑connected layers after the embedding extractor and training with a standard cross‑entropy loss.

The wav2vec2-large-robust-12-ft-emotion-msp-dim model is a fine‑tuned speech‑emotion recognizer built on top of Facebook’s wav2vec2‑large‑robust architecture.