LALAL.AI
LALAL.AI is a next-generation audio separation service powered by advanced AI technology. With a suite of innovative tools - Stem Splitter, Voice Cleaner, Voice Changer, Voice Cloner, LALAL.AI enables users to take their audio content to the next level.
Stem Splitter
The core service of LALAL.AI, Stem Splitter allows users to extract individual vocals or instruments from audio tracks. Supported instruments include: drums, bass, piano, guitar (electric and acoustic), synthesizer, and string and wind instruments
Voice Cleaner
A powerful tool for extracting clean, clear vocals from audio and video
Voice Changer
Tap into the power of AI to mimic the singing styles of famous stars
Voice Cloner
Create custom voices
Echo & Reverb Remover
Remove unwanted echo and reverb from vocals, voice recordings, songs, and videos, all in popular audio and video formats
Lead & Back Vocal Splitter
Use state-of-the-art AI technology to precisely separate lead and backing vocal
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Google Cloud Speech-to-Text
Google Cloud’s Speech API processes more than 1 billion voice minutes per month with close to human levels of understanding for many commonly spoken languages. Powered by the best of Google's AI research and technology, Google Cloud's Speech-to-Text API helps you accurately transcribe speech into text in 73 languages and 137 different local variants. Leverage Google’s most advanced deep learning neural network algorithms for automatic speech recognition (ASR) and deploy ASR wherever you need it, whether in the cloud with the API, on-premises with Speech-to-Text On-Prem, or locally on any device with Speech On-Device.
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Qwen3-TTS
Qwen3-TTS is an open source series of advanced text-to-speech models developed by the Qwen team at Alibaba Cloud under the Apache-2.0 license, offering stable, expressive, and real-time speech generation with features such as voice cloning, voice design, and fine-grained control of prosody and acoustic attributes. The models support 10 major languages, including Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, and Italian, and multiple dialectal voice profiles with adaptive control over tone, speaking rate, and emotional expression based on text semantics and instructions. Qwen3-TTS uses efficient tokenization and a dual-track architecture that enables ultra-low-latency streaming synthesis (first audio packet in ~97 ms), making it suitable for interactive and real-time use cases, and includes a range of models with different capabilities (e.g., rapid 3-second voice cloning, custom voice timbres, and instruction-based voice design).
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