Editing Vocoder Development (section)

== Key Innovations ==
Innovations in vocoders are often developments in deep learning, signal processing and machine learning. 

According to Dudley, the use of vocoders is advantageous for more secure communications and a greater number of telephone channels in the same frequency space. Digital communication made eavesdropping conversations more difficult. However, the digitization of speech required wider transmission bandwidths. The vocoder was used to reduce the speech bitrate to a number that could be handled through the average telephone channel. <ref name=":0" />

Pitch detection in vocoding was a difficulty in the late 1950s. This is necessary to synthesize speech of acceptable quality. Then, vocoders can recreate variations in tone and pitch. <ref>Gold, B., & Rabiner, L. (1969). Parallel processing techniques for estimating pitch periods of speech in the time domain. ''The Journal of the Acoustical Society of America'', ''46''(2B), 442-448.</ref> Speech is created by vibrating the vocal folds, the air that is moving and closing the mouth. The vocal fold vibrations are analyzed to find the pitch. To estimate the fundamental frequency, the Lincoln Laboratory designed an algorithm that used parallel processing, which produced accurate results. <ref name=":0" />

In a channel vocoder, formant tracking helps recreate speech. It looks at the first four formant features to estimate the speech sounds. This method can make a vocoder use less data or bandwidth and still sound good. <ref>Gold, B. (1980, April). Formant representation of parameters for a channel vocoder. In ''ICASSP'80. IEEE International Conference on Acoustics, Speech, and Signal Processing'' (Vol. 5, pp. 128-130). IEEE.</ref>

Another innovation is the speaker-dependent WaveNet vocoder that uses existing vocoder data as additional information. This method does not need to explicitly model certain aspects of speech and offers better sound quality. It successfully recovers lost information and captures source details more accurately compared to traditional vocoders. <ref>Tamamori, A., Hayashi, T., Kobayashi, K., Takeda, K., & Toda, T. (2017, August). Speaker-dependent wavenet vocoder. In ''Interspeech'' (Vol. 2017, pp. 1118-1122).</ref>

WORLD, a vocoder-based speech synthesis system, was developed in an effort to improve the sound quality of real-time applications using speech. Real-time processing has been difficult because of the high computational costs. This new system has a good sound quality and is also quick in processing. <ref name=":3">Morise, M., Yokomori, F., & Ozawa, K. (2016). WORLD: a vocoder-based high-quality speech synthesis system for real-time applications. ''IEICE TRANSACTIONS on Information and Systems'', ''99''(7), 1877-1884.</ref>