SpeakStream: Streaming Text-to-Speech with Interleaved Data
With the increasing integration of speech front-ends and large language models (LLM), there is a need to explore architectures that integrate these modalities. While end-to-end models have been explored extensively, cascaded models that stream outputs from LLMs to TTS seem to be oddly under-explored, even though they are potentially much simpler. Using traditional text-to-speech systems to convert LLM outputs to audio, however, poses a technical problem because they need entire utterances to generate sytlistic audio. In this paper we present a ‘streaming’ TTS that can generate audio from…
Contemporary text-to-speech solutions for accessibility applications can typically be classified into two categories: (i) device-based statistical parametric speech synthesis (SPSS) or unit selection (USEL) and (ii) cloud-based neural TTS. SPSS and USEL offer low latency and low disk footprint at the expense of naturalness and audio quality. Cloud-based neural TTS…
Text Normalization (TN) is a key preprocessing step in Text-to-Speech (TTS) systems, converting written forms into their canonical spoken equivalents. Traditional TN systems can exhibit high accuracy, but involve substantial engineering effort, are difficult to scale, and pose challenges to language coverage, particularly in low-resource settings. We propose PolyNorm, a…
Almost anywhere you looked, AI-based speech technologies continued to blossom in 2022, from increased interest measured in Google Trends, to surprising medical advances that suggest speech patterns can help detect some illnesses, to the variety of digital services and devices that users control with their voices. At Google Cloud, we spent…