Speech Recognition Learning Path

Definition and scope of speech recognition

Speech recognition (automatic speech recognition, ASR, or speech-to-text, STT) is a sub-field of computational linguistics focused on converting spoken language into text or other interpretable outputs. Its scope includes both the core translation of audio into linguistic units (such as words or phonemes) and related tasks that can use speech signals to support applications, such as voice user interfaces, transcription, audio search, dictation, and analyses of speaker characteristics. Within this scope, speech recognition systems are typically evaluated and designed for different operating conditions and use cases. Common application areas include direct voice input (e.g., command and control in phones, home automation, and aircraft-related contexts) as well as productivity tools (e.g., generating transcripts and searching recordings). The field also distinguishes speech recognition from voice/speaker recognition, where the goal is identifying the speaker rather than the spoken content, and it addresses challenges such as speaker variability, continuous vs. isolated speech, vocabulary size, and environmental noise.

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Voice user interfaces and direct voice input

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