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silero-vad-sherpa
Silero VAD served through the sherpa-onnx backend. Uses the same ONNX weights as the dedicated silero-vad backend, loaded through sherpa-onnx's C VAD API. Pairs with the sherpa-onnx ASR entries for round-trip audio pipelines.
Repository: localaiLicense: mit
voice-hi_IN-priyamvada-medium
A fast, local neural text to speech system that sounds great and is optimized for the Raspberry Pi 4. Piper is used in a variety of [projects](https://github.com/rhasspy/piper#people-using-piper).
Repository: localaiLicense: mit
silero-vad
Silero VAD - pre-trained enterprise-grade Voice Activity Detector.
Repository: localai
silero-vad-ggml
Silero VAD - pre-trained enterprise-grade Voice Activity Detector.
Repository: localai
parakeet-cpp-realtime-scene-speakers
Cache-aware streaming RNNT FastConformer with end-of-utterance (EOU)
detection, 120M, paired with Nemotron-3-Diarization and CED-Tiny through
the diarization_model and sound_model options. F16/Q8_0 GGUF for the
parakeet-cpp backend (C++/ggml port of NVIDIA NeMo). Use with streaming
transcription: while a turn is live, closed speaker segments and sound
events are surfaced alongside the ASR text (realtime
conversation.item.input_audio_transcription.segment and
conversation.item.sound_detection events). Live speaker/sound events only
fire during speech turns under semantic_vad; sounds between turns are not
seen by this path. License per model: transcription model NVIDIA Open
Model License, diarization model OpenMDW-1.1, CED-Tiny Apache-2.0,
WeSpeaker ResNet34 CC-BY-4.0. Also loads WeSpeaker ResNet34 through the
speaker_model option, so live speaker segments carry the name of a voice
registered with /v1/voice/register (voice-detect-wespeaker-resnet34 model)
once the speaker is identified.
Repository: localaiLicense: nvidia-open-model-license
parakeet-cpp-realtime-scene
Cache-aware streaming RNNT FastConformer with end-of-utterance (EOU)
detection, 120M, paired with Nemotron-3-Diarization and CED-Tiny through
the diarization_model and sound_model options. F16/Q8_0 GGUF for the
parakeet-cpp backend (C++/ggml port of NVIDIA NeMo). Use with streaming
transcription: while a turn is live, closed speaker segments and sound
events are surfaced alongside the ASR text (realtime
conversation.item.input_audio_transcription.segment and
conversation.item.sound_detection events). Live speaker/sound events only
fire during speech turns under semantic_vad; sounds between turns are not
seen by this path. License per model: transcription model NVIDIA Open
Model License, diarization model OpenMDW-1.1, CED-Tiny Apache-2.0.
Repository: localaiLicense: nvidia-open-model-license
parakeet-cpp-realtime-scene-tdt
Parakeet TDT 0.6B v3 (multilingual, 25 European languages) paired with
Nemotron-3-Diarization and CED-Tiny through the diarization_model and
sound_model options: one parakeet-cpp backend transcribes, labels speakers
and tags sound events. GGUF for the parakeet-cpp backend (C++/ggml port of
NVIDIA NeMo). TDT is not a streaming model, so in a realtime pipeline use
it with server_vad: set it as both transcription and sound_detection and
turn on pipeline.diarization, and each committed turn gets speaker segments
(conversation.item.input_audio_transcription.segment, with text) and
sound tags (conversation.item.sound_detection). Also labels speakers on
/v1/audio/transcriptions. Speaker labels are per turn. License per model:
transcription model CC-BY-4.0, diarization model OpenMDW-1.1, CED-Tiny
Apache-2.0.
Repository: localaiLicense: cc-by-4.0
parakeet-cpp-realtime-scene-base
Cache-aware streaming RNNT FastConformer with end-of-utterance (EOU)
detection, 120M, paired with Nemotron-3-Diarization and CED-Base (86M, the largest CED;
more confident sound tags than CED-Tiny at a small extra cost: on CPU the
live diarization + sound stream runs at 0.125 of real time against 0.103
with CED-Tiny) through
the diarization_model and sound_model options. F16/Q8_0 GGUF for the
parakeet-cpp backend (C++/ggml port of NVIDIA NeMo). Use with streaming
transcription: while a turn is live, closed speaker segments and sound
events are surfaced alongside the ASR text (realtime
conversation.item.input_audio_transcription.segment and
conversation.item.sound_detection events). Live speaker/sound events only
fire during speech turns under semantic_vad; sounds between turns are not
seen by this path. License per model: transcription model NVIDIA Open
Model License, diarization model OpenMDW-1.1, CED-Base Apache-2.0.
Repository: localaiLicense: nvidia-open-model-license
parakeet-cpp-realtime-scene-tdt-base
Parakeet TDT 0.6B v3 (multilingual, 25 European languages) paired with
Nemotron-3-Diarization and CED-Base (86M, the largest CED; about 0.03 s of
CPU per second of audio per committed turn, against 0.005 for CED-Tiny)
through the diarization_model and
sound_model options: one parakeet-cpp backend transcribes, labels speakers
and tags sound events. GGUF for the parakeet-cpp backend (C++/ggml port of
NVIDIA NeMo). TDT is not a streaming model, so in a realtime pipeline use
it with server_vad: set it as both transcription and sound_detection and
turn on pipeline.diarization, and each committed turn gets speaker segments
(conversation.item.input_audio_transcription.segment, with text) and
sound tags (conversation.item.sound_detection). Also labels speakers on
/v1/audio/transcriptions. Speaker labels are per turn. License per model:
transcription model CC-BY-4.0, diarization model OpenMDW-1.1, CED-Tiny
Apache-2.0.
Repository: localaiLicense: cc-by-4.0
piper-hi_IN-priyamvada-medium-crispasr
Piper (rhasspy VITS) Hindi voice "priyamvada", medium quality, synthesized through the CrispASR backend. Lightweight local neural TTS producing 22.05 kHz mono audio. Runs end-to-end on CPU.
Repository: localai
audio-cpp-silero-vad
Silero VAD (audio.cpp) - voice activity detection over /v1/vad. The model
ships inside the audio-cpp backend package, so installing this entry
downloads nothing.
Repository: localaiLicense: mit
audio-cpp-marblenet-vad
MarbleNet VAD (audio.cpp) - NeMo voice activity detection over /v1/vad, an
alternative to Silero with different segment boundaries. The model ships
inside the audio-cpp backend package, so installing this entry downloads
nothing.
Repository: localaiLicense: other