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Only First party#Voice
Oct 30Fri
  1. ElevenLabs Blog36

    What is turn taking in conversational AI: A guide to natural flow

    This ElevenLabs guide explains turn taking in conversational AI as the rules that determine when a voice agent should reply, hold the floor, or stay silent, relying on adaptive timing, voice activity detection, and semantic analysis rather than strict silence timers. It describes how ElevenAgents detects speech, silence, and intent, handles interruptions and backchannels, and lets teams tune settings like turn eagerness and silence timeouts to avoid premature endpointing, dead air, and false triggers. It also covers measuring quality through interruption rate and response latency, citing a 142 ms median time from request to audible speech with Eleven v4 Turbo and a 200 ms average human turn gap from Journal of Cognition research.

  2. ElevenLabs Blog52

    Introducing SFX v3 in ElevenCreative and ElevenAPI

    ElevenLabs launched SFX v3, its newest sound effects model, which handles prompts describing multiple sounds more reliably, generates music and vocals more convincingly, and produces cleaner, more natural audio than SFX v2 in benchmark testing. It is available now in ElevenCreative (Flows, the Sound Effects tab, Studio, the Music Editor, and the mobile app) and through ElevenAPI for developers.

Oct 29Thu
  1. Hugging Face Blog36

    Granite Switch 4.1.1 — Update models like you update software

    Granite Switch 4.1.1 is a backwards-compatible patch release to Granite Switch 4.1 that adds an updated Granite Speech ASR model covering multilingual speech-to-text across 10 languages with native punctuation and capitalization, plus an updated Decision adapter in granitelib-core with improved performance on the Jev Decision Index test set. Apart from training the new ASR model and Decision adapter, nothing was recomputed and the base model is untouched. The team says it is working on tutorials and an Adapter SDK so developers and third-party providers can build their own adapters.

  2. Hugging Face Blog58

    Introducing AnySpeechRecognizer and AnyDecisionModel: Open Models for Speech and Decisions on Apple Platforms

    The author announces two Swift packages: AnySpeechRecognizer, which mirrors Apple's SpeechAnalyzer API while allowing alternative engines such as NVIDIA's Parakeet and Alibaba's Qwen3-ASR running locally on Core ML, plus speaker diarization via NVIDIA's Streaming Sortformer; and AnyDecisionModel, which answers yes-or-no, multiple-choice, and rating-scale questions with typed results and probabilities from backends including MLX, Core AI, llama.cpp, Jev, and Ollama. Both can download open models from the Hugging Face Hub and run them on device, require Swift 6.2 and macOS 26 or iOS 26 or later, and are published on GitHub.

  3. ElevenLabs Blog23

    Conversational AI in banking: Use cases, benefits, examples

    This guide explains how banks use conversational AI—NLP-based chat and voice agents that understand natural language, pull account context, and escalate to humans when needed—for 24/7 support, onboarding, disputes, and fraud alerts. It cites CFPB findings on early bank chatbots, McKinsey figures on reduced handling time and call volume, and ElevenLabs customer examples from Customers Bank and Klarna, while detailing security standards such as SOC 2 Type II, ISO 27001, PCI DSS, and Zero Retention Mode.

  4. ElevenLabs Blog55

    How your transcript knows where each word is spoken

    ElevenLabs introduced Cue, a forced alignment model that places every character in an audio file on a precise timeline, powering its Scribe speech-to-text family and available through a Forced Alignment API. ElevenLabs says Cue was more accurate than every aligner it tested across all 29 benchmark languages, handles recordings of any length in a single pass, and aligns an hour of audio in under a second. It also aligned songs in English, French, Spanish and German in one pass, placing 92.7% of words within 0.3 seconds of the label.

  5. Baseten Blog55

    The fastest, lowest-cost batch transcription with Qwen3-ASR

    Baseten optimized Qwen3-ASR 1.7B, an Apache 2.0 open-weight speech recognition model supporting over 30 languages and 22 Chinese dialects with a 5.4% average WER on the Open ASR Leaderboard, for batch transcription on a single RTX PRO 6000. The optimized stack transcribes 7x more audio per second than out-of-the-box vLLM at high concurrency, reaching 2,645x real-time factor on 5-minute clips and 3,128x on hour-long files, with median latency for 5-minute clips at 64 concurrent requests falling from 50 seconds to 7.3 seconds. Baseten reports a cost of about $0.0013 per audio hour, 8x lower than the same model on vanilla vLLM and roughly 277x less than popular closed-weight providers.

  6. Databricks Blog36

    Voice Agents are here. Context turns them into real customer value.

    Databricks argues that voice agents are now practical because synthetic voices sound natural and can respond within roughly 200 milliseconds, but that most enterprise AI investment has focused inward on employee assistants rather than customer conversations. It describes a prototype in which LiveKit carries calls, Deepgram handles speech-to-text, ElevenLabs adds voices, and Databricks supplies the "brain" that looks up caller context, applies business rules, and records each decision, built on context, ontology, and governance. The post outlines three pillars—grounding answers in business data, fast and slow AI decision-making including the ai_decide capability, and a learning loop from recorded calls—and points to the open-source DIVA blueprint on GitHub and a suggested 90-day pilot.

Oct 28Wed
  1. Hugging Face Blog78

    NVIDIA Nemotron 3.5 Transcribe and Granary v2: Intelligent Multilingual Transcription You Can Prompt and Adapt

    NVIDIA released Nemotron 3.5 Transcribe, an open-weight, promptable model that handles transcription in 40 languages, translation of 31 to or from English, speaker attribution in 13 languages, and audio question answering in one checkpoint, running on a single NVIDIA GPU. It ranks first among open-weight models on the Hugging Face Open ASR Leaderboard for English at 5.33% average WER and posts the lowest diarization error rate on David AI's 21-language leaderboard. The release also includes Granary v2, an open data curation pipeline covering 463,062 hours across 48 languages, and NeMo Speech fine-tuning recipes that cut held-out WER by 45.8% relative to the best prompt in a medical case study.

    Why it matters: It documents concrete benchmark standings, an open data pipeline, and a reproducible fine-tuning recipe for teams evaluating or adapting open speech models.

  2. NVIDIA Newsroom58

    NVIDIA RTX Spark Windows Laptops Gain New Models, Agent Tools and Games

    NVIDIA announced RTX Spark laptops from ASUS, Dell, HP, Lenovo, Microsoft and MSI, combining a Blackwell RTX GPU and Grace CPU with up to 128GB unified memory and up to 1 petaflop of FP4 AI performance, starting at $2,599. Updates include the open-weight Nemotron 3.5 Transcribe speech model, Liquid AI's LFM3 family with day-zero support, and resource management controls in NVIDIA App for sharing GPU resources between foreground apps and background agents. Phantom Blade Zero launches Oct. 28 with ray tracing and DLSS 4.5, and RTX Remix 1.6 brings path tracing and DLSS to Minecraft Java Edition 1.21.1.

  3. ElevenLabs Blog32

    Voice AI for Karnataka

    At the first ElevenLabs Summit India in Bengaluru, ElevenLabs signed an MoU with the Government of Karnataka to bring voice AI into state public services, covering exploration of pilots for grievance redressals, public helplines and entitlement schemes in Kannada and 13 other official Indian languages. The agreement also includes deploying ElevenLabs' safety framework—covering deepfake detection, watermarking, consent, limits on voice cloning and fraud prevention—and supporting residents who have lost the ability to speak through free lifetime licences under the One Million Voices program.

  4. ElevenLabs Blog24

    Lettuce cuts creative ad production from over a week to under a minute with ElevenLabs

    Lettuce's growth team uses Ads Engine in ElevenCreative to pull its best-performing Meta ads, generate new versions in about 45 seconds, and push them back to market, with the creative director and a performance marketer reviewing each ad before it runs. The company reports roughly 75% lower creative costs and 40% to 60% lower cost per lead compared with other creative running in similar periods, and its current top-performing Meta ad came from the 15th to 20th iteration of an original asset.

  5. ElevenLabs Blog58

    ElevenLabs and adELA bring free voice restoration to Spain

    ElevenLabs announced a partnership with adELA, Spain's leading ALS association, to give people living with ALS across Spain free access to its voice restoration and preservation technology, the first Spanish initiative under the ElevenLabs Impact Program and the first country where the technology is available through a national patient association. Eligible people diagnosed with ALS can create a digital version of their voice by recording new samples if their speech hasn't yet changed significantly, or by uploading old recordings if it already has. The article profiles Aníbal Martín, an aviation engineer and programming teacher with ALS who used the technology to create a digital version of his voice, saying "Being able to hear my own voice means being able to remain myself."

  6. ElevenLabs Blog38

    How to build an AI voice assistant: Brand-aligned voice AI

    This guide explains how to build an AI voice assistant by connecting speech to text, an LLM, and text to speech into one real-time pipeline, then adding a knowledge base, business tools, system instructions, and fallback rules. It covers architecture choices between raw APIs and the managed ElevenAgents platform, latency targets below 500 ms with voice activity detection, caller verification, human handoff, brand voice customization, and pre-launch testing for latency, interruptions, accuracy, and safety. Post-launch metrics such as containment, escalation rate, word error rate, hallucination rate, and CSAT are recommended for continued improvement.

  8. ElevenLabs Blog22

    What shoppers choose once they’ve tried a retail AI agent

    ElevenLabs ran three studies across the UK, US, Canada, Australia, Europe, South Africa and Latin America in which most shoppers completed a real task with a live voice agent before answering questions. Nearly half chose speaking and hearing replies going forward, and voice was the top choice on all six shopping tasks, though comparing products split shoppers almost evenly; when told an agent had failed once, the share asking for a person rose from 24% for a late delivery to 61% for a wrong charge. Shoppers wanted a written record of resolutions, and 60% said they would abandon an agent entirely if there were no visible way to reach a person.

Oct 27Tue
  1. ElevenLabs Blog50

    Why voice wins for complex, stressful conversations

    ElevenLabs compared voice calls and chat across hundreds of production agents and found that in conversations longer than two minutes, voice succeeded 32% more often than text chat and resolved successful long conversations about one third quicker. In a simulated canceled-flight scenario, 85% of 98 participants preferred voice, citing speed of resolution and empathy. A 16% reduction in average end-to-end latency across 315 agent conversations correlated with a 26% lift in success rate, with calls ending within 15 seconds falling from 21.1% to 3.8%.

  2. ElevenLabs Blog38

    When AI comes knocking, how governments can prepare

    ElevenLabs describes "agentic flooding"—an AI-driven rise in the volume or complexity of requests to public services—citing researchers who tracked 84 cases across 11 countries, and says it released synthetic voice detection in ElevenAgents to tell whether a caller is human or AI and set handling rules. It argues governments should add capacity rather than friction, citing Midland, Texas's AI civic concierge Jacky and Czech benefits and employment hotlines where agents handle roughly 5,000 calls per day and resolve about 85% independently.

  3. Apple Newsroom48

    Siri AI is available in more languages starting today

    Apple Intelligence with Siri is available when the device and Siri language are set to Chinese (simplified or traditional), Danish, Dutch, English, French, German, Italian, Japanese, Korean, Norwegian, Portuguese, Spanish, Swedish, Turkish, or Vietnamese. Siri AI is in beta in iOS 27.2, iPadOS 27.2, macOS 27.2, watchOS 27.2, and visionOS 27.2, requires an Apple Intelligence-enabled device set to a supported language, and is currently unavailable in the EU on iOS, iPadOS, and watchOS. Some server-based Apple Intelligence features are subject to daily usage limits, with expanded access to be offered for a fee in the future.

  4. PyTorch Blog34

    Optimizing Streaming Speech Recognition on Arm® Edge Devices with ExecuTorch

    This PyTorch blog case study takes the multilingual Nemotron 3.5 streaming ASR model from PyTorch to ExecuTorch and profiles it on a Google Pixel 11, measuring how chunk size and precision affect streaming WER and processing time. Enabling Arm SME2 cut whole-recording processing time from 9.79 to 4.61 seconds for FP16 (2.12x) and from 5.20 to 3.24 seconds for QC8W (1.61x), with GEMM driving most of the gain, while longer chunks improved accuracy at the cost of latency. ETDump and Arm Streamline were combined to attribute speedups to operators and confirm which KleidiAI SME2 microkernels actually ran.

Oct 23Fri
  1. AWS Machine Learning Blog43

    Amazon Polly delivers a major upgrade to its Generative engine

    Amazon Polly's upgraded Generative engine is now generally available, offering more expressive and accurate speech with low latency as a drop-in upgrade that requires no code changes. It adds 14 new voices across 9 locales, including the first generally available Generative voices for Hindi and Finnish, bringing the catalog to 57 voices across 11 languages and 25 locales, with expansion to AWS GovCloud (US-West). Pricing is unchanged, and the engine continues to support SSML and the Bi-Di Streaming API.

  2. AWS Machine Learning Blog38

    Stream low-latency speech from AI agents using Kokoro TTS on Amazon SageMaker AI

    This AWS post describes streaming each sentence an agent produces to a hosted Kokoro-82M text-to-speech model on a SageMaker AI real-time endpoint, so synthesis starts on the first sentence instead of waiting for the full response. It covers bidirectional WebSocket handling, an incremental sentence chunker, and two transports for returning audio to the browser, reporting that incremental sending cut mean time to first audio byte from 329.3 ms to 156.7 ms in isolation and made bidi mode 2.4 to 3.5 times faster than batch in a deployed agent.

  3. AWS Machine Learning Blog32

    Stop guessing auto scaling targets for TTS on Amazon SageMaker AI

    This AWS post deploys Kokoro-82M, an 82-million-parameter non-autoregressive TTS model, as a custom container on an Amazon SageMaker AI real-time endpoint via AWS CDK stacks, then replaces a guessed auto scaling target with values derived from two live measurements: Q_max (the highest per-instance concurrency that still meets a 3,000 ms p95 time-to-first-audio SLO, measured at 50) and T_total (end-to-end scale-out time, measured at 260.2 s and planned against 320.2 s). Scaling uses the native ConcurrentRequestsPerModel metric, and a five-command tool chain (drift, qmax, ttotal, plan, validate) computes the scale-out threshold (37.5), scale-in threshold (25.0) and asymmetric cooldowns by arithmetic. The authors note the methodology generalizes to other latency-sensitive, concurrency-bound real-time SageMaker AI endpoints, while the specific numbers hold only for Kokoro-82M on ml.g5.xlarge.

Oct 21Wed
  1. Hugging Face Blog58

    Granite Speech 5.0: Transcribe, Translate, and Attribute more Accurately and Faster

    IBM released granite-speech-5.0-2b, a new speech-language model trained on 390,000 hours of public audio that transcribes English, French, German, Spanish, Portuguese, and Japanese, translates to and from English in those languages plus English to Italian and Mandarin, and supports language-ID prompting and keyword lists up to 2,000 terms. It also updated granite-speech-5.0-470m-turboctc, which adds multilingual transcription and native punctuation and capitalization and reaches 19,870 RTFx on the Open ASR Leaderboard (about 1.6x faster than at launch), and granite-speech-4.1-2b-plus, which cuts word diarization error rate and speaker-attributed WER by 7% each and long-form WER by 24%. All three ship under Apache 2.0 with support in Transformers, vLLM, llama.cpp, and mlx-audio.

Oct 20Tue
  1. Mistral AI80

    Voxtral 3

    Mistral introduces Voxtral 3, a family of speech-to-text and text-to-speech models plus a LiveKit-based voice agent SDK that combines listening, reasoning, tool calling and speaking in one real-time streaming pipeline. It includes Voxtral Small Transcribe 3 for multilingual transcription with diarization and context biasing, Voxtral Mini TTS 3 for expressive speech in 35+ languages and 50+ dialects, and Pro Voice adaptation from 30 minutes of audio. It is available via Mistral's EU-hosted API or self-deployment, with pricing from $0.0035/min for batch transcription to $13 per 1M characters for TTS.

    Why it matters: The announcement details concrete model capabilities, benchmarks and pricing for teams evaluating real-time voice agents and sovereign speech deployment.