Model Detail
speaker-diarization-community-1
▼ 2.8%speaker-diarization-community-1 is an audio model released by pyannote. The model is registered under the automatic-speech-recognition pipeline tag on Hugging Face, distributed under the permissive cc-by-4.0 license.
The cc-by-4.0 license is permissive, allowing commercial deployment and derivative work without per-seat fees, though attribution requirements still apply.
Downloads of speaker-diarization-community-1 have moved -2.8% over the past 24 hours, -3.6% over the trailing seven days. That is a slight downtrend, consistent with normal cooling as newer models compete for the same workloads. These numbers are signal, not guarantee — week-over-week download counts on Hugging Face also reflect mirror traffic, CI scrapes, and one-off benchmarking runs.
speaker-diarization-community-1 is best fit for speech recognition, transcription, or speech synthesis depending on the task head. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.
You Are the Trigger: Speaker-Activated Backdoors
arXiv:2610.27210v1 Announce Type: new Abstract: Speech models are increasingly used as an interface to AI systems, from transcription tools to voice agents. Existing audio backdoors require an attacker to introduce triggers at inference time. We study a different threat model in which the attacker c
Slots Are Not Speakers: Training-Free Speaker Linking for Frozen Streaming Diarizers
arXiv:2610.28053v1 Announce Type: cross Abstract: This paper presents a causal, training-free linker that allows a frozen streaming diarizer to track more speakers than it has output slots. Streaming end-to-end diarizers such as Streaming Sortformer emit a fixed number N of concurrent speaker slots.
Beyond Two Tracks: Speaker-Anchored Full-Duplex Dialogue Recovery
arXiv:2610.27109v1 Announce Type: cross Abstract: Spoken interaction is moving from alternating turns to full-duplex conversation, where an agent listens while speaking. Learning this coordination requires natural dialogue with persistent speaker-resolved tracks, a data requirement that remains diff
ShlokaDhara: A Multi-Speaker Sanskrit Speech Corpus for Learning Meter-Aware Prosody in Text-to-Recitation
arXiv:2610.26929v1 Announce Type: cross Abstract: Sanskrit verse recitation is governed by $\textit{Chandas}$, a strict prosodic framework defined by rhythmic $\textit{Laghu}$ (light) and $\textit{Guru}$ (heavy) syllables. Because existing Sanskrit speech datasets prioritize ASR or conversational TT
TTS-Q: Speaker-Aware Post-Training Quantization of Text-to-Speech Diffusion Transformers
arXiv:2610.12474v3 Announce Type: replace-cross Abstract: Zero-shot text-to-speech (TTS) can clone a voice from seconds of audio. Yet the quality comes from billion-parameter diffusion transformers whose size and multi-step sampling put them out of reach of the on-device, assistive, and real-time ap
Anuvani-Diarization: Zero Shot Speaker Diarization and Annotation Conventions Across 22 Languages
arXiv:2610.20327v2 Announce Type: replace Abstract: India's 22 scheduled languages are spoken by over a billion people in conversations that mix languages, often within one turn, overlap freely, and take place over telephones, in meetings, and in media. Knowing who spoke when, the task of speaker di
