Pocket TTS is a lightweight (~100M param) continuous-latent autoregressive TTS model from Kyutai, based on the CALM paper (arXiv:2509.06926). Unlike codebook-based TTS models, Pocket TTS emits continuous float vectors — no discrete tokens, no softmax sampling: - **FlowLM backbone** — causal transformer (1024D, 16 heads, 6 layers; 24 layers for the French preview, RoPE, GELU) operating at 12.5 Hz - **Consistency head** — SimpleMLPAdaLN (512D, 6 ResBlocks) with timestep embedding → one-step LSD decode → 32-dim continuous latent vectors - **Mimi VAE decoder** — SEANet upsample convolutions + 2-layer transformer → 24 kHz PCM - **Mimi VAE encoder** *(voice-cloning builds only)* — SEANet downsample + 2-layer transformer + speaker projection → reference conditioning - **Text tokenizer** — SentencePiece BPE (4000 vocab, embedded in GGUF) Single GGUF file — no separate codec companion needed (Mimi weights and the tokenizer are embedded). Pocket TTS is zero-shot: it clones the timbre of a short reference clip. The **voice-cloning builds** (the files *without* `novc` in the name) embed the Mimi VAE **encoder** and speaker projection needed to condition on a reference; the English-only `novc` builds omit that encoder and are ~20 MB smaller.
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GGUF / ggml conversions of `Qwen/Qwen3-ASR-0.6B` for use with the `qwen3-asr-main` CLI from **CrispStrobe/CrispASR**. This is the **first speech-LLM** in the CrispASR family — every other model in the set uses a dedicated CTC / transducer / encoder-decoder. The Qwen3-ASR runtime ships with a persistent KV cache so per-token decode is O(1) in cache size, not O(N) full re-forwards. All quantisations produce the correct transcript on `samples/jfk.wav`: > And so, my fellow Americans, ask not what your country can do for you; ask what you can do for your country.
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Qwen3-ASR-1.7B is a multilingual speech recognition model supporting 30 languages + 22 Chinese dialects, with support for speech, singing voice, and songs with background music. Audio inputs up to 5 minutes. `qwen3-asr-1.7b-q4_k.gguf` was re-baked with the 24-layer **audio encoder kept at Q8_0** (previously Q4_K like the LLM body; ~0.15 GB larger). The earlier Q4_K export could emit an **empty transcript** (or, on longer audio, a repeated phrase) while still reporting success (CrispASR #240) — the same sub-8-bit encoder drift diagnosed in #218. Encoder-output cosine vs the F16 reference (jfk): **0.9632 → 0.9989** min, **0.9913 → 0.9998** mean — i.e. the tower is back to near-lossless and decode no longer degenerates. The Q8_0 and F16 files were never affected. On JFK speech sample (11s, English): - Q4_K: 0.2x realtime on CPU (4 threads) - Perfect transcription accuracy
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GGUF conversions of `Qwen/Qwen3-ForcedAligner-0.6B` — a single-pass forced aligner that takes any (audio, transcript) pair and predicts per-word/per-token timestamps. Reuses the Qwen3-ASR audio encoder + 28-layer LLM body but swaps the lm_head from `(vocab, d)` to `(5000, d)`: each ` ` placeholder you embed in the input gets a 5000-class softmax over `class * 80 ms` timestamps. Plug it into CrispASR via `-am qwen3-forced-aligner-*.gguf` to get word-level timing on **any** transcription backend — voxtral, voxtral4b, qwen3-asr, granite, parakeet, canary, cohere, even whisper. It's an alternative to the existing `canary-ctc-aligner` second-pass with broader language coverage and 80-ms resolution. The CrispASR C++ runtime auto-detects which variant a loaded GGUF is by reading the lm_head shape from `output.weight.ne[1]` — no separate backend, no separate library.
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GGUF / ggml conversion of `Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice` for use with **CrispStrobe/CrispASR**. The CustomVoice variant is the **fixed-speaker** sibling of `Qwen3-TTS-12Hz-0.6B-Base`: instead of cloning a voice from a 3 s reference WAV (the Base path), it ships **9 baked speaker tokens** picked via a `--voice ` flag. No ECAPA forward, no codec encoder, no reference audio required. Two of the speakers (`dylan`, `eric`) carry Chinese-dialect overrides (Beijing / Sichuan) that re-route `language_id` when synthesising Chinese-or-auto. Pair this with the codec at `cstr/qwen3-tts-tokenizer-12hz-GGUF` — the talker emits 16-codebook RVQ codes that the codec decoder renders to 24 kHz PCM.
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GGUF / ggml conversion of `Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice` for use with **CrispStrobe/CrispASR**. The 1.7B sibling of `cstr/qwen3-tts-0.6b-customvoice-GGUF`. Same fixed-speaker pattern (9 baked speakers, no ECAPA, no reference WAV), but on the 1.7B talker — `hidden=2048`, `head_dim=128`, with a `small_to_mtp_projection` MLP that maps the 2048-d talker hidden state down to the 1024-d code predictor input space. Pair this with the codec at `cstr/qwen3-tts-tokenizer-12hz-GGUF` — the talker emits 16-codebook RVQ codes that the codec decoder renders to 24 kHz PCM.
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GGUF / ggml conversions of `Qwen/Qwen3-TTS-Tokenizer-12Hz` for use with the `qwen3-tts` backend in **CrispStrobe/CrispASR**. Qwen3-TTS-Tokenizer-12Hz is the separate **speech tokenizer / codec** used by the Qwen3-TTS family: - 10 supported languages: `zh en ja ko de fr ru pt es it` - 12.5 Hz, 16-codebook speech representation - used for reference-audio encoding, voice-pack baking, and final waveform decode - Apache-2.0 licence
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