{"id":121971,"date":"2025-02-17T14:22:05","date_gmt":"2025-02-17T12:22:05","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/opublikovana-ai-model-sinteza-rechi-zonos-podderzhivayushhaya-klonirovanie-golosa"},"modified":"2025-02-17T14:22:05","modified_gmt":"2025-02-17T12:22:05","slug":"opublikovana-ai-model-sinteza-rechi-zonos-podderzhivayushhaya-klonirovanie-golosa","status":"publish","type":"post","link":"https:\/\/prohoster.info\/en\/blog\/news\/opublikovana-ai-model-sinteza-rechi-zonos-podderzhivayushhaya-klonirovanie-golosa","title":{"rendered":"The AI voice synthesis model Zonos has been released, supporting voice cloning.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Zyphra has released the first beta version of its speech synthesis AI model, Zonos, under the Apache 2.0 license. The toolkit offered with the model supports a voice cloning feature, allowing speech to be synthesized in the desired voice, for which the model only needs a 30-second reference recording of the speaker's voice. Synthesis is supported in English, Japanese, Chinese, French, and German. <\/p>\n

The model encompasses 1.6 billion parameters and has been trained on 200,000 hours of audio recordings. It supports the synthesis of monotone speech (as in audiobooks) and emotional speech (as in live conversation), as well as prefix-based synthesis (where an audio recording with the beginning of the speech is provided, based on which the model synthesizes the continuation according to the specified text, replicating the original characteristics of the speech, such as continuing to speak in whispers). <\/p>\n

The output generates sound with a sampling rate of 44kHz. It supports the substitution of synthesizable inserts to simulate performances with multiple speakers or to build interactive dialogues, as well as the addition of tags to control speech speed, pitch, and emotional expressions such as joy, fear, sadness, and anger. <\/p>\n

According to the developers, the quality of the generated speech does not lag behind or exceeds all publicly available open-source and commercial synthesis systems (tests provide comparisons with ElevenLabs, Cartesia, and FishSpeech). A drawback noted is a higher concentration of audio artifacts, such as coughing, breathing sounds, or creaking, at the beginning or end of the generated audio material. <\/p>\n