Speech synthesis is the artificial production of human speech. A computer system used for this purpose is called a speech synthesizer, and can be implemented in software or hardware products. A text-to-speech (TTS) system converts normal language text into speech; other systems render symbolic linguistic representations like phonetic transcriptions into speech. Synthesized speech can be created by concatenating pieces of recorded speech that are stored in a database. Systems differ in the size of the stored speech units; a system that stores phones or diphones provides the largest output range, but may lack clarity. For specific usage domains, the storage of entire words or sentences allows for high-quality output. Alternatively, a synthesizer can incorporate a model of the vocal tract and other human voice characteristics to create a completely "synthetic" voice output.
Speech synthesis systems were first developed in the late 1950s. The first commercial systems were introduced in the early 1960s, and by the late 1970s, text-to-speech systems were in common use. Today, there are many different systems available for a variety of applications.
What are the speech synthesis methods?
There are many different speech synthesis methods, each with its own strengths and weaknesses. One popular method is formant synthesis, which creates the desired sound by manipulating the frequencies of the formants (the resonance peaks) in the speech signal. This method is often used for generating synthetic speech that sounds natural and realistic. Another popular method is concatenative synthesis, which stitches together fragments of recorded speech to create the desired sound. This method can produce very natural-sounding speech, but it can be time-consuming and expensive to create the required database of recorded speech fragments.
Why do we need speech synthesis?
Speech synthesis is the artificial production of human speech. A computer system used for this purpose is called a speech synthesizer, and can be implemented in software or hardware products. A text-to-speech (TTS) system converts normal language text into speech; other systems render symbolic linguistic representations like phonetic transcriptions into speech.
Synthesized speech can be created by concatenating pieces of recorded speech that are stored in a database. Systems differ in the size of the stored speech units; a system that stores phones or diphones provides the largest output range, but may lack clarity. For specific usage domains, the storage of entire words or sentences allows for high-quality output.
To create a speech synthesizer, one needs a voice font, which is a database of recorded speech samples. The samples are stored as digital audio, and are typically in a linear PCM format. The voice font is used to synthesize speech, which is output as digital audio. The quality of the synthesized speech depends on the quality of the voice font.
What is speech synthesis in NLP?
Speech synthesis is the artificial production of human speech. A computer system used for this purpose is called a speech synthesizer, and can be implemented in software or hardware products.
NLP speech synthesis is the application of NLP techniques to speech synthesis. This can involve the use of NLP algorithms to analyze speech data and generate synthetic speech that sounds natural and intelligible. NLP speech synthesis can be used to create synthetic voices for applications such as text-to-speech, voice recognition, and voice-based interface systems.
What is the difference between speech synthesis and speech recognition?
Speech synthesis is the artificial production of human speech. A computer system used for this purpose is called a speech synthesizer, and can be implemented in software or hardware. A text-to-speech (TTS) system converts normal language text into speech; other systems interpret spoken words to produce written text.
Speech recognition is the ability of a machine or program to identify words and phrases in spoken language and convert them to a machine-readable format.