Addressing Hallucinations in Speech Synthesis LLMs with the NVIDIA NeMo T5-TTS Model
Addressing Hallucinations in Speech Synthesis LLMs with the NVIDIA NeMo T5-TTS Model | NVIDIA Technical Blog
“NVIDIA NeMo has released the T5-TTS model, a significant advancement in text-to-speech (TTS) technology. Based on large language models (LLMs), T5-TTS produces more accurate and natural-sounding speech. By improving alignment between text and audio, T5-TTS eliminates hallucinations such as repeated spoken words and skipped text. Additionally, T5-TTS makes up to 2x fewer word pronunciation errors compared to other open-source models such as Bark and SpeechT5.
Listen to T5-TTS model audio samples.
NVIDIA NeMo is an end-to-end platform for developing multimodal generative AI models at scale anywhere—on-premises and on any cloud.
The role of LLMs in speech synthesis
LLMs have revolutionized natural language processing (NLP) with their remarkable ability to understand and generate coherent text. Recently, LLMs have been widely adopted in the speech domain, using vast amounts of data to capture the nuances of human speech patterns and intonations. LLM-based speech synthesis models produce speech that is not only more natural, but also more expressive, opening up a world of possibilities for applications in various industries.
However, similar to their use in text domain, speech LLMs face the hallucinations challenges, which can hinder their real-world deployment…”