Search “Speech”

Built on LiveKit's open-source framework and global edge network, Clerk AI scales enterprise voice agents to 1,000+ concurrent calls with no pre-provisioning and sub-500ms response times. Its ScreenSense achieves 97% accuracy in call screening detection on Apple and Android devices, while TrueReach voicemail detection exceeds 98% accuracy. The platform natively supports 30+ languages with automatic switching mid-conversation. It has achieved SOC 2 Type II certification and includes built-in TCPA

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AWS partner Cartesia provides voice models on AWS based on State Space Models (SSMs) with first-byte latency under 100ms: Sonic text-to-speech produces its first audio in about 90ms, supports more than 44 languages and voice cloning from 10-second audio samples, and Ink speech-to-text supports native turn detection and streaming transcription. SSMs achieve native streaming inference through fixed-size hidden states and token-by-token processing, avoiding the latency that comes from Transformers

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Edge0 has released the open-weight voice cloning TTS model Audio8-TTS-Realistic, with 601M parameters, supporting 23 languages, with weights and code released under Apache 2.0. The model requires only 1 reference audio clip and its corresponding text for zero-shot voice cloning, and can also directly generate speech when no reference voice is available. Self-reported results show an average error rate of 4.86% on the CV3 nine-language benchmark, lower than Qwen3-TTS-1.7B's 7.73%, but it lags beh

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The 10-person startup Phonic has released a speech model, Phonic-1, which it says can execute queries and bookings before the caller has finished speaking. The model tops the Artificial Analysis speech-to-speech leaderboard with a score of 87.1, 0.2 points higher than xAI's Grok Voice 3.0, with a customer service task completion rate of 79.9% and a first-audio latency of 0.61 seconds. Phonic says it scored 90.2 on the Cekura call test set, but the public Cekura leaderboard lists Phonic v1 at 68.

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Artificial Analysis evaluations show that Phonic's Phonic 1 (High) ranks first among 22 models on the Speech to Speech Index with 87.1 points, leading Grok Voice 3.0's 86.9 points by a narrow margin. The model ranks first on the Tau Voice agent task with 79.9%, leading the second place by 5.4 percentage points; it ranks third on Big Bench Audio with 98.9%, and its Time to First Audio is 0.61 seconds. Phonic 1 is available through the Phonic API, with input audio costing $0.07 per minute and $4.2

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OpenBMB ambassador @emwstudio has open-sourced an ESP32-S3 cockpit-style attitude indicator project that uses MiniCPM5-2B to generate tower replies and VoxCPM2 to synthesize speech. The device sends push-to-talk audio over Wi-Fi to a Mac-side pipeline, where Qwen3-ASR performs local recognition, and the reply audio then streams back to the device speaker. The tower incorporates simulated flight data such as altitude, speed, heading, pitch, and roll, and points out inconsistencies between request

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Artificial Analysis evaluations show that Drama 3, released by Fish Audio, has an Elo of 1,278 in the Provider Voice scenario of Text to Speech (1,512 arena appearances), ranking 6th overall and 1st among open-weight models; in the Controlled Voice scenario, its Elo is 1,085 (1,958 appearances), ranking 12th overall and 1st among open-weight models. On pronunciation robustness, Drama 3 ranks 1st with 94.6% (2,157 rated clips), higher than the 93.2% of Ming-3.0-tts and Drama 3 Preview. Its genera

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On October 28, NVIDIA released Nemotron 3.5 Transcribe, an open-weight speech model that can transcribe audio in 40 languages, translate speech, and identify speakers, and developers can control the transcription format with natural language instructions without retraining. The model consists of a Transformer speech encoder, a speaker diarization model, and the Nemotron 3.5 Lightning language model, with approximately 4.3 billion activated parameters, and the released checkpoint is labeled 30B-A

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Gnani AI has released its automatic speech recognition model Prisma v3.0, supporting nine Indian languages including Hindi and Bengali as well as English, and capable of transcribing multilingual conversations with intra-sentence Hindi-English code-mixing. On the Vistaar benchmark, the model achieves a macro-average WER of 16.93, lower than ElevenLabs Scribe v2's 19.98, Microsoft Azure Speech-to-Text's 20.51, and Deepgram Nova 3's 26.57. It offers four transcription modes—Verbatim, Transcribe, C

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NVIDIA has released the open-weight speech transcription model Nemotron 3.5 Transcribe, with 30B total parameters and 4B activated parameters. On Artificial Analysis's non-streaming speech transcription leaderboard, it achieves a 2.8% AA-WER, tying for first among open-source models with Mistral's Voxtral Small. On the speech agent dialogue dataset AA-AgentTalk, it leads Voxtral Small's 2.3% with 1.8%. Its activated parameters are 4B, while Voxtral Small's are 24B; other open-source models of co

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