AudioLMGoogle
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SeeduplexByteDance
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About
AudioLM is a pure audio language model that generates high‑fidelity, long‑term coherent speech and piano music by learning from raw audio alone, without requiring any text transcripts or symbolic representations. It represents audio hierarchically using two types of discrete tokens, semantic tokens extracted from a self‑supervised model to capture phonetic or melodic structure and global context, and acoustic tokens from a neural codec to preserve speaker characteristics and fine waveform details, and chains three Transformer stages to predict first semantic tokens for high‑level structure, then coarse and finally fine acoustic tokens for detailed synthesis. The resulting pipeline allows AudioLM to condition on a few seconds of input audio and produce seamless continuations that retain voice identity, prosody, and recording conditions in speech or melody, harmony, and rhythm in music. Human evaluations show that synthetic continuations are nearly indistinguishable from real recordings.
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About
Seeduplex is a native full-duplex speech large language model built on a new “listen while speaking” framework for more natural, fluid, and precisely paced voice interaction. Unlike traditional half-duplex systems that alternate between listening and replying, it continuously receives and understands user-side audio, allowing it to listen and speak simultaneously while tracking the broader acoustic environment. Its high-precision interference suppression distinguishes genuine user interaction from background noise, broadcasts, navigation prompts, side conversations, and overlapping voices, reducing false responses and false interruptions in complex settings. Seeduplex also combines speech and semantic features for adaptive endpoint detection, helping it recognize when a user is thinking, hesitating, correcting themselves, or has actually finished speaking. It can wait patiently through reflective pauses, respond quickly once an utterance ends, and stop smoothly when interrupted.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Audio researchers and developers needing a solution for creating realistic speech and music continuations directly from raw audio
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Audience
Automotive and smart-device developers that need natural, interruption-aware voice assistants capable of operating reliably in noisy environments
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationGoogle
United States
research.google/blog/audiolm-a-language-modeling-approach-to-audio-generation/
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Company InformationByteDance
Founded: 2012
China
seed.bytedance.com/en/seeduplex
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Categories |
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Integrations
Google Opal
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