New Research Aligns Text to Speech Effortlessly | Google

Author(s): Dr. Mandar Karhade, MD. PhD.

Originally published on Towards AI.

Overcome Sequence length mismatch without explicitly specifying it.

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Training a text-speech (multimodal Model) has its own problems. Given the audio sample rate is high, the sequence length for audio is a lot longer than the corresponding text. To train both text and audio simultaneously, we need to overcome this disparity (lazily without having to generate explicitly annotated training data). This paper solves that problem.

The last year has seen sastonishing progress in text-prompted image generation premised on the idea of a cross-modal representation space in which the text and image domains are represented jointly.

In Automatic Speech Recognition (ASR),… Read the full blog for free on Medium.

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Published via Towards AI