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5 articles

01 ·Audio & Speech·★ MEMBER·PAPER·14 min read Paper Walkthrough: VoiceMem — A Left Brain and a Right Brain for Voice Agents, at Zero Added Latency A from-scratch walkthrough of VoiceMem, a memory system for real-time speech interaction. A factual 'left brain' and an affective 'right brain' run in parallel, and the whole retrieval is hidden inside the silence a VAD already waits out — which is how it wins at a top-5 budget. 02 ·Audio & Speech·★ MEMBER·PAPER·13 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·★ MEMBER·PAPER·13 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. 04 ·Audio & Speech·★ MEMBER·PAPER·12 min read Speech Synthesis from Scratch — From Text to a Voice Speech synthesis invents a waveform tens of thousands of times longer than the handful of characters it starts from. This walks through why naive regression fails (one-to-many and phase), why text → mel spectrogram → waveform became the standard split, and how a few seconds of reference audio is now enough to carry a voice. 05 ·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.