What does DBSS mean in SOFTWARE
Diphone Based Speech Synthesis (DBSS) is a method of artificial speech synthesis which uses recordings of the transitions between different speech sounds, called diphones. Diphones are made up of two phonemes, where a phoneme is the smallest unit of sound that can affect the meaning of an utterance when it's changed. In DBSS, these transitions between phonemes known as diphone are used as the basis for synthesized speech.
DBSS meaning in Software in Computing
DBSS mostly used in an acronym Software in Category Computing that means Diphone Based Speech Synthesis
Shorthand: DBSS,
Full Form: Diphone Based Speech Synthesis
For more information of "Diphone Based Speech Synthesis", see the section below.
Essential Questions and Answers on Diphone Based Speech Synthesis in "COMPUTING»SOFTWARE"
What Is Diphone Based Speech Synthesis?
Diphone Based Speech Synthesis (DBSS) is a method of artificial speech synthesis which uses recordings of the transitions between different speech sounds, called diphones.
What Are Diphones?
A diphone is two phonemes, where a phoneme is the smallest unit of sound that changes the meaning when changed in an utterance.
How Does DSPC Work?
In DBSS, these transitions between phonemes known as diphone are used as the basis for synthesized speech.
How Does This Differ From Other Methods Of Speech Synthesis?
Other methods such as concatenative synthesis and articulatory synthesis allow for more natural sounding results because they take into account how various parameters interact to create a whole word or phrase. However, due to its simplicity and relative computational efficiency, diphone-based speech synthesis has remained popular in applications that do not require highly realistic results.
What Are The Limitations Of Using This Method?
There are some limitations with relying on transitions between static articulations - dynamic parameters such as duration, voicing strength and nasalization may be missed or misrepresented with this approach. Additionally, due to its limited number of source units and lack of context awareness, some forms of variation such language-specific accentuation may not be possible to achieve even with additional processing steps like formant modeling or vocoding.
Final Words:
Despite its limitations, diphone based speech synthesis has remained popular because it provides relatively efficient ways to generate reproducible synthetic voices from small databases that can then be used in applications that do not require complex features or highly realistic results. Furthermore, by combining this method with other techniques it's possible to produce more natural-sounding results than what would be achievable with either approach alone.