Search: “voice-api”

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Google Releases Gemini 3.8 Live and 3.8 Live Extended Thinking for Production Grade Voice Agents

Google launches Gemini 3.8 Live and Extended Thinking speech-to-speech models for production voice agents, topping speech-to-speech benchmarks.

Google released Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking, native speech-to-speech models for real-time voice agents, available hosted via the Gemini Live API and AI Studio. Extended Thinking ranks #1 on Artificial Analysis' Speech-to-Speech Quality Index with 82.6, scores 68.6% on τ-Voice, 35.1% on Sierra's τ-Voice-banking, and 97.7% on Big Bench Audio. The models support asynchronous function calling, near-real-time visual context, alphanumeric precision, and 97 languages, priced at $0.005/min audio input and $0.018/min audio output. All generated audio carries Google DeepMind's imperceptible SynthID watermark.

MarkTechPost·Sep 15, 20:53 UTC · 16h agoModel release 3 sources

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Introducing the Agents API

OpenAI launched the Agents API in public beta, exposing the Codex agent harness, managed sandboxes, and multi-agent orchestration to developers.

OpenAI introduced the Agents API in public beta, giving developers the same agent harness and infrastructure that powers Codex through a single API call specifying task, model, tools, and environment. It supports OpenAI-managed sandboxes, customer infrastructure, or partner environments from providers including Cloudflare, Modal, E2B, Vercel, Oracle, DigitalOcean, Blaxel, Daytona and Runloop. Features include automatic context compaction for long sessions, tool search and programmatic tool calling to reduce token usage, and multi-agent support for parallel subagents. The harness is open-source Codex code; there are no extra API fees during beta, with developers paying only for tokens and tools used.

OpenAI News·updated Sep 11, 08:11 UTC · 5d ago·first Sep 10, 00:00 UTC · 6d agoAI tools & infra 4 sources

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Build more natural voice experiences with GPT‑Live‑1 in the API

OpenAI releases GPT-Live-1 in the API, a full-duplex voice model that handles interruptions natively and delegates reasoning to backend models.

OpenAI launched GPT-Live-1 in the API, a single-model full-duplex voice system that listens and speaks simultaneously, replacing chained STT-LLM-TTS architectures. It improves Full Duplex Bench performance by 30 percentage points over GPT-Realtime-2.1 and ranks #1 on Tau3 when paired with GPT-6 Astra at medium reasoning effort. Early partner Speak reported nearly 80% fewer interruptions in language tutoring. The API release costs $0.05 per minute for the front-end voice layer and supports telephony, native ASR transcripts, keyword biasing, and expanded voice and language options.

OpenAI News·updated Sep 12, 14:26 UTC · 3d ago·first Sep 10, 00:00 UTC · 6d agoModel release 10 sources1

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Gradium Launches Voice Design: Write a Prompt, Get a Brand New Synthetic Voice in Seconds

Gradium, a Kyutai spinout, launched Voice Design, generating custom synthetic voices from text descriptions in seconds across five languages.

Gradium, a Paris-based voice AI company spun out of Kyutai, launched Voice Design, which generates new synthetic voices from 1-500 character text descriptions in seconds without needing reference audio or speaker consent. The feature is live in the Gradium API and Studio, free on every plan including the free tier, and kept voices run on the standard streaming TTS endpoint at the same latency as catalog voices. Vendor-run blind pairwise listening tests across 7,627 comparisons report a 72.6% win rate, 13.6 points ahead of ElevenLabs at 59.0%, placing first in all five tested languages, with the largest margins on regional accents such as Quebecois French (97%).

MarkTechPost·Sep 9, 07:29 UTC · 7d agoAI industry

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Building and Evaluating Fixed-Voice Thai TTS from Synthetic Speech

Researchers distill a compact 82M-parameter Thai TTS from synthetic OmniVoice data, enabling on-device fixed-voice synthesis without reference audio.

The paper uses a large voice-cloning model (OmniVoice) as a synthetic data source to train Wayu-Paxa-TTS-Edge, an 82M-parameter fixed-voice Thai TTS student. The model achieves 68.2% Challenge-Set Keyword Accuracy (85.5% of Gemini 3.1), 91.4% pause precision, and CERs of 3.7% on Thai and 1.1% on English. It outperforms its teacher on pause placement and is open-sourced with its evaluation framework.

Hugging Face daily papers·Sep 2, 20:00 UTC · 13d agoAI research

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MP-Bench: Evaluating Voice Agents as a Multiparty Conversation Participant

MP-Bench is the first benchmark for voice agents in multiparty conversations, finding real-time agents near chance on turn-taking.

MP-Bench is the first benchmark designed to objectively evaluate conversational speech systems as active participants in multi-party conversations. It assesses agents on turn-taking awareness and response appropriateness, with comprehension-based question-answering as a complementary evaluation. Benchmarking 12 voice agents shows real-time agents score at or below 22% on multiparty comprehension and remain near chance on multiparty turn-taking.

arXiv cs.AI / cs.LG / cs.CL·Sep 11, 17:11 UTC · 4d agoAI research2

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Build Low-Latency Multilingual Voice Agents: Open Weights & Full Deployment Control with NVIDIA Magpie TTS

NVIDIA's Magpie TTS open-weight multilingual speech model enables low-latency voice agents with full deployment control.

Hugging Face's blog highlights NVIDIA Magpie TTS, an open-weights multilingual text-to-speech model designed for building low-latency voice agents. The open licensing gives developers full deployment control, allowing self-hosted multilingual speech for agentic applications. The post walks through building voice agents with the model.

Hugging Face Blog·Aug 10, 16:25 UTC · Aug 10, 2026Model release

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Safe word: What is it and why do you need one?

ESET recommends pre-agreed family safe words to counter AI voice-clone scams such as virtual kidnapping, as one-in-four Americans report receiving deepfake calls.

ESET outlines how scammers use just seconds of audio scraped from social media or work content to create convincing voice clones, with a Hiya report finding one-in-four Americans received a deepfake voice call in the past 12 months. Common schemes include virtual kidnapping calls mixing cloned voices with sobbing and background noise. A pre-agreed, non-OSINT-discoverable safe word, plus callback verification via known numbers and 2FA, reduces success rates of these frauds.

ESET WeLiveSecurity·Sep 9, 09:00 UTC · 7d agoPhishing & fraud in the wild

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The Machines Are Calling: Measuring Automated and Synthetic Voices in Unwanted Inbound Calls

Voice honeypot measurement finds at least 26.9% of unwanted US inbound calls open with machine voices, 13.1% with fresh synthetic speech.

An interactive voice honeypot using language-model personas on real US numbers recorded 10,987 calls over 66 days, following the FCC's February 2024 ruling that AI-generated voices fall under the TCPA. Of 7,233 greeted calls, 13.8% opened with recordings replayed from other calls and 13.1% with fresh audio labeled synthetic, with replays making up 45% of the detector's flagged rate. Synthetic openings concentrated in lead-generation spam (33.8%) rather than fraud (21.1%), and only 0.44% of calls disclosed automation. Prevalence tracked how long a bait number had circulated, and campaigns outlasted their numbers, with one synthetic voice serving nine campaigns.

arXiv cs.CR·Sep 10, 06:28 UTC · 6d agoResearch

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Building a Production Greek-English Speech Recognizer

Engineering report details Sophea, a production Greek-English ASR reaching 4.26% WER on public English sets via ROVER ensemble and data-pipeline calibration.

Across 23 training iterations, two architectures, and nine production gates, no single data composition passed all gates; a three-model ROVER ensemble reached 9 of 9 gates and cut overlapping-speech WER from 53.35% to 37.87%. Calibrating an audio-quality filter against in-domain anchors reduced discarded scored Greek audio from 98.7% to 10.6%, and a pre-registered ablation traced a hallucination defect to one training-data package. The sophea/asr-k1 preview arbiter lists 4.26% average WER on eight public English test sets and 25.88% WER on live Greek noisy traffic; no weights or training data are released.

Hugging Face daily papers·Sep 10, 20:00 UTC · 5d agoAI research

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What Did I Just Say? Self-Listening for Full-Duplex Speech Models

Researchers propose Self-Listening, a full-duplex speech approach feeding realized model speech back as input to improve interruption recovery.

Full-duplex spoken language models can listen and speak simultaneously, but asynchronous text generation, speech synthesis, and playback cause mismatches between what a model believes it said and what the user heard. The paper defines the resulting recovery problem as anchor interruption and proposes Self-Listening, which interleaves user speech, model text, and played speech as input streams. The authors also release AnchorSpeech, a benchmark with homogeneous training and test splits tracking which ordered response items were actually spoken. Experiments show self-listening models achieve better anchoring performance than full-duplex baselines.

Hugging Face daily papers·Sep 3, 20:00 UTC · 12d agoAI research

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StepAudio 3 Realtime Technical Report

StepAudio 3 Realtime debuts an audio-language model with Think-While-Speaking reasoning, delivering full-duplex voice dialogue with top benchmark results.

StepAudio 3 Realtime is an audio-language foundation model built around a continuous listen-converse-think-act loop for real-time spoken interaction. Think-While-Speaking runs private reasoning in parallel with speech, reaching a 73.0 macro average on StepAudioChat in reasoning mode. The model reports 90.6 on MMSU, 98.9 overall on the Artificial Analysis Full-Duplex Bench, and 56.0% macro task success on tau-Voice. An integrated Voice Agent handles asynchronous tool execution without disrupting dialogue flow.

Hugging Face daily papers·Sep 11, 20:00 UTC · 4d agoAI research

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Amazon launches Alexa+ in India with Hindi support

Amazon launched its generative AI Alexa+ assistant in India with Hindi support in Early Access, free for Prime customers after testing.

Amazon announced that Alexa+, its generative AI-powered conversational assistant, is now available in India in Early Access with Hindi and English support, including mid-sentence language switching and long-form context retention. The assistant handles multi-step tasks such as ordering groceries via Amazon Now and controlling smart home devices, with integrations including Swiggy, District, MakeMyTrip, EazyDiner, Amazon Music, and JioSaavn. It will be free for Prime members after the testing period and cost about $20.85 per month for non-Prime customers. Amazon is targeting India's 600 million-plus Hindi speakers, and says smart device adoption grew 20% year over year.

TechCrunch · AI·10:34 UTC · 2h agoAI industry

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Gemini Live audio

Google released Gemini 3.8 Live speech-to-speech models; Simon Willison built a library-free browser web UI for real-time voice conversations with them.

Google released Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking, two new speech-to-speech models comparable in shape to OpenAI's GPT-Live family. Simon Willison had GPT-6 Astra Extra High build him a web UI for testing the models, supporting model and voice preset selection, optional system prompts, and interrupting the model mid-speech. The implementation uses no libraries and talks directly to Google's wss://generativelanguage.googleapis.com BidiGenerateContent WebSocket endpoint.

Simon Willison·Sep 15, 22:47 UTC · 14h agoModel release

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Amazon Prime Video’s new AI tech matches lips to dubbed audio

Amazon Prime Video launched AI lip-sync dubbing aligning actors' mouth movements with human-dubbed audio, starting with the English dub of Maxton Hall.

Prime Video's new feature combines AI and visual effects technologies to make lip movements match translated speech, currently available for seasons 1-2 of the German series Maxton Hall worldwide and planned for additional titles, with season 3 arriving December 9. Amazon previously piloted AI-aided dubbing in English and Spanish across 12 movies and shows last year. Meta and YouTube have recently launched similar AI auto-dubbing features with optional lip sync for creators.

The Verge · AI·Sep 9, 13:00 UTC · 6d agoAI industry

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microsoft/VibeVoice-ASR-Streaming-7B — new model trending #27 on Hugging Face

Microsoft released VibeVoice-ASR-Streaming-7B, an open streaming ASR model with speaker attribution, custom hotwords, and support for 10 languages under MIT license.

Microsoft Research released VibeVoice-ASR-Streaming-7B on Hugging Face, a unified streaming speech recognition model that continuously transcribes who said what as speech arrives. The 7B model supports customized hotwords for domain-specific terms and 10 languages including Chinese, English, French, German, Italian, Japanese, Korean, Portuguese, Russian, and Spanish. Code is available at github.com/microsoft/VibeVoice with a live demo, and a technical report is on arXiv (2609.02812). The model is licensed under MIT.

Hugging Face trending models·Sep 2, 15:46 UTC · 13d agoModel release1

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AWS Introduces Pizza Bot: An Open Source Inbox for Background AI Agents

AWS open-sourced Pizza Bot, a self-hosted inbox app for background AI agents with approval gating and multi-provider model support.

AWS released Pizza Bot under Apache 2.0 after earlier versions served over 2,000 Amazon employees for meeting prep, email drafting, and research. The app provides macOS, Windows, and Linux desktop builds plus browser and terminal clients talking to a Hono API server, with LangGraph/DeepAgents checkpoints preserving thread state and approval pauses. It supports Amazon Bedrock, Anthropic, Google Gemini, OpenAI, OpenRouter, and Ollama, exposes external tools via MCP servers, and lets skill authors gate actions behind approve/edit/reject flows.

MarkTechPost·Sep 13, 08:10 UTC · 3d agoAI tools & infra

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BreezeBlue/Breeze-TTS-2 — new model trending #19 on Hugging Face

BreezeBlue open-weights Breeze TTS 2, a bilingual text-to-speech model it ranks #1 among open-weight models on the Artificial Analysis TTS leaderboard.

BreezeBlue released open weights and Apache 2.0-licensed PyTorch inference code for Breeze TTS 2 on 2026-08-25. The text-to-speech model supports English and Chinese, voice cloning, reference-free voice design, voice direction, and inline vocal events like (laugh) and (sigh). Reported performance includes #1 open-weight ranking on the Artificial Analysis Elo leaderboard, under 40 ms time-to-first-audio, a 0.32 real-time factor on an NVIDIA H100, and about 7.7 GiB GPU memory for eager inference.

Hugging Face trending models·Aug 25, 16:39 UTC · 21d agoModel release

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Show HN: Nari Qwen3-TTS and Qwen3-ASR – High accuracy, low latency and cost

Nari Labs claims top Coval voice AI benchmark rankings with low-latency, low-cost Qwen3-ASR and Qwen3-TTS inference endpoints.

Nari Labs says its Qwen3-ASR Fast endpoint ranks #1 in Coval's time-to-final-segment latency (p50 44 ms) with 3.6% WER at $0.12/hour, behind only AssemblyAI Universal 3.5 Pro on accuracy. Its Qwen3-TTS Fast ranks #2 in time-to-first-audio (p50 63 ms) and #1 in WER at 3.8%, priced at $10 per 1M characters. The company reports beating the official Qwen3 TTS Flash Realtime endpoint (8.8% WER, 692 ms median TTFA) and Baseten's dedicated endpoint (6.0% WER, 101 ms). Public beta APIs are moving to paid general availability with $20 in credits for existing accounts.

Hacker News · security·Sep 14, 16:07 UTC · 1d agoAI tools & infraHN 21↑ · 7 comments

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Meta Introduces Muse, a Personal AI Agent That Runs on Its Own Dedicated Secure Cloud Computer

Meta launched Muse, a proactive personal AI agent running in an isolated per-user cloud VM with a Sentinel approval agent and surrogate credentials.

Meta introduced Muse, a consumer agent that performs long-horizon tasks like email, travel booking, and bill negotiation, rolling out in the US on iOS, Android, muse.ai, and WhatsApp with free and paid tiers. Each user gets a dedicated Muse Secure VM where the agent runs in a systemd-nspawn cell, while a separate Sentinel agent approves every network request at layer 4/7 and injects real credentials only at the network boundary. The underlying Muse Spark 1.3 model, which Meta says cuts tool calls by ~20% and tokens by ~25% versus 1.2 and is near state-of-the-art on prompt-injection resistance, is available via Meta Model API, with open weights on the roadmap.

MarkTechPost·Sep 9, 04:38 UTC · 7d agoAI industry

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Nuha-Speech: Building General-Purpose Arabic Speech-LLMs

Nuha-Speech initiative builds general-purpose Arabic speech-LLMs using a 1.5M-sample speech QA corpus and fine-tuned Qwen-Omni variants.

The paper introduces Nuha-Speech, an initiative covering dataset construction, model training, and evaluation for Arabic speech large language models. The authors built an Arabic Speech Question-Answering corpus of over 1.5 million training samples and used it for supervised fine-tuning of Qwen-Omni model variants at multiple scales. A tailored evaluation framework with diverse tasks and metrics is designed to assess Arabic speech capabilities under limited resource constraints.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:50 UTC · 5d agoAI research1

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Motion-Omni: End-to-End Joint Speech and Full-Body Motion for Spoken Dialogue

Researchers introduce Motion-Omni, an end-to-end model generating speech with synchronized full-body motion, responding 5.4x faster than cascade pipelines.

Motion-Omni is an end-to-end framework in which a spoken dialogue model outputs facial expressions and hand, upper-body, and lower-body motion directly from the hidden states that produce speech, replacing two-stage cascade pipelines. Trained on 422,856 quality-ranked pseudo-labeled pairs (1,402 hours) with a Qwen2.5-7B-Instruct backbone, Motion-Omni-Q7 matches its teacher cascade within 2% on reference-free motion metrics, achieves a 2.62% word error rate, and runs faster than real time (RTF=0.78). The authors also release the SwDA-500 dataset and the first public evaluation protocol for stochastic open-ended full-body spoken dialogue.

Hugging Face daily papers·Aug 27, 20:00 UTC · 19d agoAI research1

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ChatGPT can now connect to your personal apps to mimic writing style

OpenAI is testing ChatGPT Writing Style, which mimics a user's voice using writing samples from connected Gmail, Slack, and Drive accounts.

OpenAI confirmed it is testing a Writing Style feature for ChatGPT that learns a user's voice from writing samples in connected apps. The onboarding flow references Messaging (Slack), Documents (Google Drive and Notion), and Email (Gmail) as example sources. It resembles Anthropic's Styles personalization feature but draws on existing writing inside connected services rather than uploaded samples. The feature is available to a small group of users with no announced general rollout date.

BleepingComputer·Sep 7, 10:36 UTC · 9d agoAI industry

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Flirty OnlyFans promoters on X may be using AI to appear human

Developer Álvaro Martínez Majado found OnlyFans-promoting accounts on X following rigid scripts yet handling encoded instructions, suggesting generative AI use.

Investigation of flirty X accounts promoting OnlyFans pages showed near-identical openers across accounts plus dynamic behaviors: answering a hexadecimal-encoded instruction with "Pineapple" and failing an exact 12-character count test in an LLM-like pattern. The accounts also sent personalized voice notes reading supplied timestamps and usernames, consistent with automated text-to-speech. Evidence suggests a hybrid scripted/AI system, though no model, provider, or operator was identified.

Malwarebytes Labs·Sep 7, 11:18 UTC · 9d agoAI safety & security

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Hacked Voice Remote Becomes

Hackers compromised a voice-controlled remote control and repurposed it, highlighting security gaps in connected consumer devices.

Infosecurity Magazine's headline indicates a voice-controlled remote was hacked and turned to another purpose. The full article text was unavailable, so technical details, victim, and actor remain unconfirmed. The item underscores risks around consumer IoT and smart-home peripherals.

Infosecurity Magazine·Aug 19, 00:00 UTC · 28d agoThreat actor in the wild

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