#spectrogram

3 articles

01 ·Audio & Speech·★ MEMBER·PAPER·9 min read Paper Walkthrough: Dynamic Band Splitting — Letting Each Mixture Decide Where the Frequency Bands Go Band-split source separators carve the spectrum into hand-designed frequency bands and use the same carving for every input. DBS keeps the number of bands fixed but predicts where the boundaries go, mixture by mixture. We walk through boundary scoring, hard Top-K, weighted pooling and full-resolution reconstruction, then read the results on three datasets and the limits. 02 ·Audio & Speech·FREE·PAPER·14 min read Representing Sound — Mel Spectrograms and Audio Tokens Why speech models never eat raw waveforms, and what they eat instead: the chain from short-time Fourier transform to the mel scale to the log to discrete tokens. Covers the window-length tradeoff, why MFCCs dropped the DCT, how acoustic and semantic tokens differ, and the config mismatches that silently wreck audio in production. 03 ·Audio & Speech·FREE·11 min read Speech Recognition from Scratch — From Waveform to Text How a stream of numbers from a microphone becomes words, starting from zero: spectrogram features, the alignment problem that CTC solved, autoregressive encoder-decoder models, and Whisper — in the order history solved them.