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.

History

The history of speech synthesis goes back to the 18th century with the development of acoustic-mechanical devices, such as the speaking machines by Wolfgang von Kempelen. In the 20th century, electronic devices and computer software led to significant advances in the field, culminating in the development of formant synthesis and concatenative synthesis methods in the latter half of the century.

Types of Speech Synthesis

There are primarily two types of speech synthesis techniques: formant synthesis and concatenative synthesis.

• Formant synthesis does not use human speech samples at runtime. Instead, the speech output is created using an acoustic model. Parameters such as fundamental frequency, voicing, and noise levels are controlled to generate speech waveforms from scratch.
• Concatenative synthesis involves the concatenation of segments of recorded speech. Typically, a large database of recorded speech is needed, from which the synthesizer selects segments to construct the output speech.

Applications

Speech synthesis has a wide range of applications including but not limited to:

• Assistive technology for individuals with vocal impairments or reading disabilities.
• Telecommunication systems, such as voice response systems.
• Language learning tools, where it provides pronunciation examples for language learners.
• Virtual assistants and smart speakers, providing user interaction through spoken commands.

Challenges

Despite advancements, speech synthesis faces several challenges:

• Achieving natural-sounding speech, particularly in terms of prosody and intonation.
• The synthesis of emotions and speech in various environmental contexts.
• The development of multi-language and accent capabilities.

Future Directions

Future research in speech synthesis may focus on improving the naturalness and expressiveness of synthesized speech, developing more efficient algorithms for voice conversion, and enhancing the ability of speech synthesis systems to convey emotions and personality.

See Also

• Natural Language Processing
• Voice Recognition
• Artificial Intelligence