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# Speech-to-Text

Speech-to-text is the process of translating spoken words into text. It is used in many contexts to analyze, search, and process audio content, including:

- The command and control of mobile devices
- Interactive voice systems for automated call handling
- Dictation of letters, memoranda, and other electronic text documents
- Audio and video search, where the search for specific terms or concepts is performed on the transcript
- Subtitles or closed captions for video
- High-level analysis of phone calls in contact centres

Speech-to-text is an imperfect process and the global research community is still trying to perfect it. Hence all automated systems that use speech-to-text are prone to errors.

There are several factors that affect the success rates of speech-to-text. These include:

- Audio quality metrics, such as signal bandwidth, background noise, and distortions introduced as part of the recording and storing processes
- Overlapping speech from different speakers
- The articulation clarity of the speaker and the speed of their speech
- In some cases, the specific dialect as well as any non-native characteristic of the speaker

There are several methods for measuring the success of speech-to-text:

- Word error rate (or the complementary word accuracy rate)
- Command success rate
- General or specific word recall and precision rates

Speech-to-text is language dependent.

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