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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

Seed-Music is an integrated framework that enables the generation and editing of high-quality music, allowing for the creation of both vocal and instrumental pieces from various multimodal inputs such as lyrics, style descriptions, sheet music, audio references, or vocal prompts. This innovative system also facilitates the post-production editing of existing tracks, permitting direct alterations to melodies, timbres, lyrics, or instruments. It employs a combination of autoregressive language modeling and diffusion techniques, organized into a three-stage pipeline: representation learning, which encodes raw audio into intermediate forms like audio tokens and symbolic music tokens; generation, which translates these diverse inputs into music representations; and rendering, which transforms these representations into high-fidelity audio outputs. Furthermore, Seed-Music's capabilities extend to lead-sheet to song conversion, singing synthesis, voice conversion, audio continuation, and style transfer, providing users with fine-grained control over musical structure and composition. This versatility makes it an invaluable tool for musicians and producers looking to explore new creative avenues.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Google Opal Yes 

Integrations

Google Opal No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

Google

Country

United States

Website

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

Vendor Details

Company Name

ByteDance

Founded

2012

Country

China

Website

seed.bytedance.com/en/seed-music

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Product Features

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