Following on Ethan Mollick's post sharing an article on Text-to-Speech (TTS) models (converting written books into audio), the "voice" they produce is a synthetic one created by the model itself, and it's #not a #copy of any specific #human voice.
TTS models are trained on text data in the sense that they learn to convert written text into spoken words.
TTS models are trained on a large dataset of text, often containing transcripts of spoken language. This text data is used to teach the model how words and phrases are pronounced.
TTS models learn the #phonetic characteristics of words and sentences. They understand the #pronounciation of individual #words and how they should be connected when spoken together.
TTS models also learn #prosody, which includes aspects like #intonation, #stress, and #rhythm in #speech. This helps them generate speech that #sounds more #natural and #expressive.
The #voice in TTS models is usually not a specific human voice. Instead, it's a #simulated #voice created by the model based on the phonetic and prosodic information it has learned. These models have a neutral or generic voice that does #not #replicate any particular person's voice.
When you input text into a TTS system, it uses the knowledge it has learned from the training data to #synthesise #speech. It combines phonetic information, prosody, and other #linguistic #rules to generate the audio.
Some TTS systems allow you to choose from different voices. These voices are variations of the model's synthetic voice, with different prosodic patterns, accents, or speaking styles. They are not recordings of human voices but rather modifications of the model's synthetic voice.
#audio #audiobooks #narrator
#speech #syntheticdata
A good thing done by AI: turning 5,000 public domain ebooks into audio books that sound like they were read by humans.
I’ve sampled a couple, and the quality is quite impressive. Books here: aka.ms/audiobook
Academic paper here: https://lnkd.in/e2PhuaUG
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1moThanks for the repost Dave!