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Speech technology


Speech technology is a type of computing technology that enables an electronic device to recognize, analyze and understand spoken word or audio. This is typically done by inputting digital sound signals and matching its pattern against a library of stored patterns.

Speech technology relies on the concepts of signal processing and machine learning. Signal processing is used to extract relevant information from speech, such as speaker characteristics, background noise and frequency. Machine learning is then applied to these listening devices to recognize and analyze the speech signals to perform the desired output, such as returning an automatic response.

Due to the fact that speech is a primary form of communication, the growth of speech technology is an important step towards harnessing unstructured voice data. Subfields of speech technology include speech recognition, speech verification, real time speech to text conversion, interactive voice response (IVR), speech synthesis and speech analytics.

Speech technology applications

With the progression of artificial intelligence solutions for enterprises, speech technology has many applications in all sectors, including law, healthcare, security, finance, enterprise and personal use. A few specific examples include:

  • Speech technology and speaker verification solutions can be applied to law enforcement techniques to identify and validate a person's voice.
  • Companies are able to apply speech technology such as speech to text and IVR functionalities to streamline customer service and support
  • Healthcare providers can use speech technology devices to aid patients that are visually impaired or hard of hearing.
  • Personal use voice assistants such as Siri, Google Home and Amazon Alexa are devices that offer individualized speech technology experiences.
  • Various careers, including speech technologists, speech engineers and speech pathologists, rely heavily on speech technology to collect more technical audio components like sample rate, signal to noise ratio and modulation.



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