---

license: other

license_name: mixed-see-model-card

license_link: LICENSE

tags:

• speaker-recognition
• speaker-verification
• speaker-embedding
• voice-analysis
• gguf
• ggml
• localai

library_name: gguf

---

voice-detect-gguf

GGUF models for the voice-detect backend of LocalAI.

Each .gguf here is a self-contained, metadata-driven model produced by

voice-detect.cpp, a standalone

C++/ggml engine for speaker recognition and voice analysis. No Python, PyTorch, or

ONNX runtime is needed at inference time: the GGUF carries the weights verbatim plus

the forward-graph topology in its KV metadata, and the C++ engine replays it. One

Kaldi-compatible 80-dim FBank front end feeds every speaker encoder; only the encoder

graph changes between models.

• Source code commit: 1db1759572c90faef6f3a78c36b5941a096a9f89 (voice-detect.cpp)
• Format: GGUF, general.architecture = "voicedetect"
• Dtype: F32 (full precision, exact vs the reference)
• Consumed by: LocalAI voice-detect backend

License - read before use

These models carry different licenses depending on their source weights. The four

speaker encoders are commercial-friendly; the two wav2vec2 analysis heads are

non-commercial, research-only. Pick what matches your use case.

| Model | Source | License | Commercial use |

|---|---|---|---|

| ecapa-tdnn-voxceleb.gguf | SpeechBrain spkrec-ecapa-voxceleb | Apache-2.0 | Yes |

| wespeaker-resnet34-voxceleb.gguf | WeSpeaker VoxCeleb ResNet34 | CC-BY-4.0 | Yes (with attribution) |

| eres2net-base-zh-cn.gguf | 3D-Speaker ERes2Net base | Apache-2.0 | Yes |

| campplus-zh-cn.gguf | 3D-Speaker CAM++ | Apache-2.0 | Yes |

| emotion-wav2vec2-superb-er.gguf | audeering wav2vec2 (emotion) | CC-BY-NC-SA-4.0 | No (research only) |

| age-gender-wav2vec2-audeering.gguf | audeering wav2vec2-large-robust (age/gender) | CC-BY-NC-SA-4.0 | No (research only) |

> The two wav2vec2 analysis heads (emotion, age/gender) are redistributed under

> their upstream CC-BY-NC-SA-4.0 terms and are for **research / non-commercial use

> only**. The four speaker encoders (ECAPA-TDNN, WeSpeaker, ERes2Net, CAM++) are

> commercial-friendly.

Models

ecapa-tdnn-voxceleb.gguf - ECAPA-TDNN, 192-d

The primary speaker-verification anchor. SpeechBrain spkrec-ecapa-voxceleb, an

ECAPA-TDNN trained on VoxCeleb, producing a 192-d L2-normalized speaker embedding.

License: Apache-2.0.

wespeaker-resnet34-voxceleb.gguf - ResNet34, 256-d

WeSpeaker ResNet34 trained on VoxCeleb, producing a 256-d embedding. Strong general

speaker verification. License: CC-BY-4.0 (attribution).

eres2net-base-zh-cn.gguf - ERes2Net, 512-d

3D-Speaker ERes2Net (base), a Res2Net backbone with attentional feature fusion,

producing a 512-d embedding. License: Apache-2.0.

campplus-zh-cn.gguf - CAM++, 192-d

3D-Speaker CAM++, a lightweight context-aware masking D-TDNN, producing a 192-d

embedding. Fast on CPU and edge. License: Apache-2.0.

emotion-wav2vec2-superb-er.gguf - wav2vec2 emotion head

A wav2vec2 transformer that returns an emotion-class distribution for an utterance

(the analyze path, not an embedding). License: CC-BY-NC-SA-4.0, research only.

age-gender-wav2vec2-audeering.gguf - wav2vec2 age/gender head

audeering wav2vec2-large-robust-24-ft-age-gender: a wav2vec2 transformer returning

an age estimate and a gender distribution for an utterance. License: CC-BY-NC-SA-4.0,

research only.

Parity

Each model was validated against its reference (SpeechBrain / WeSpeaker / 3D-Speaker /

audeering, via torch or ONNX) before upload. The embedding gate is cosine >= 0.9999

(and an identical verification verdict). At F32 the match is exact.

| Model | Dtype | Embedding cosine | Result |

|---|---|---:|---|

| ecapa-tdnn-voxceleb.gguf | f32 | 1.000000 | PASS |

| wespeaker-resnet34-voxceleb.gguf | f32 | 1.000000 | PASS |

| eres2net-base-zh-cn.gguf | f32 | 1.000000 | PASS |

| campplus-zh-cn.gguf | f32 | 1.000000 | PASS |

| emotion-wav2vec2-superb-er.gguf | f32 | 1.000000 | PASS |

| age-gender-wav2vec2-audeering.gguf | f32 | 1.000000 | PASS |

Usage

These models are intended to be installed through the LocalAI model gallery

(voice-detect-ecapa-tdnn, -wespeaker-resnet34, -eres2net, -campplus,

-emotion-wav2vec2, -age-gender-wav2vec2) and run by the voice-detect backend,

which exposes speaker embed / verify / identify and analyze (age, gender,

emotion). See the LocalAI and

voice-detect.cpp documentation.