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Description

AudioLM is an innovative audio language model designed to create high-quality, coherent speech and piano music by solely learning from raw audio data, eliminating the need for text transcripts or symbolic forms. It organizes audio in a hierarchical manner through two distinct types of discrete tokens: semantic tokens, which are derived from a self-supervised model to capture both phonetic and melodic structures along with broader context, and acoustic tokens, which come from a neural codec to maintain speaker characteristics and intricate waveform details. This model employs a series of three Transformer stages, initiating with the prediction of semantic tokens to establish the overarching structure, followed by the generation of coarse tokens, and culminating in the production of fine acoustic tokens for detailed audio synthesis. Consequently, AudioLM can take just a few seconds of input audio to generate seamless continuations that effectively preserve voice identity and prosody in speech, as well as melody, harmony, and rhythm in music. Remarkably, evaluations by humans indicate that the synthetic continuations produced are almost indistinguishable from actual recordings, demonstrating the technology's impressive authenticity and reliability. This advancement in audio generation underscores the potential for future applications in entertainment and communication, where realistic sound reproduction is paramount.

Description

Qwen-Audio-3.0-TTS-Flash is a real-time version of Qwen-Audio-3.0-TTS, specifically optimized for interactive uses with a first-packet latency around 300 milliseconds. It boasts support for 16 different languages and enhanced fidelity for various Chinese dialects. In multilingual assessments, Flash achieves the lowest average word error rate and character error rate in its category at 3.87, demonstrating impressive clarity while maintaining the unique characteristics of different speakers across multiple languages. Developers can efficiently manage the output using straightforward language instructions, rather than fine-tuning acoustic settings manually, which allows them to influence aspects like emotion, role, scenario, pace, projection, and tone through intuitive prompts. Additionally, inline tags enable the integration of specific non-verbal cues, making this model ideal for an array of applications, including conversational agents, storytelling, gaming, dubbing, and other expressive speech scenarios. Voice cloning capabilities are also included, designed to perform well even with less-than-perfect reference audio; targeted acoustic simulation effectively reduces background noise and reverberation while ensuring the original voice's tonal qualities are preserved. Overall, this advanced technology allows for a more versatile and engaging audio experience across various platforms and applications.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Alibaba Cloud Model Studio
Google Opal

Integrations

Alibaba Cloud Model Studio
Google Opal

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Google

Country

United States

Website

research.google/blog/audiolm-a-language-modeling-approach-to-audio-generation/

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

alibabacloud.com

Product Features

Product Features

Alternatives

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