Speech Recognition
Quick Answer
Speech recognition, also known as automatic speech recognition (ASR), converts spoken audio into text. Modern ASR handles accents, background noise, multiple speakers and domain-specific vocabulary far better than systems from even a few years ago.
In Depth
What Speech Recognition really means
Contemporary ASR systems are based on end-to-end neural networks trained on tens of thousands of hours of audio. They support real-time transcription, speaker diarisation (who said what) and word-level timestamps.
Speech recognition is a foundation for voice assistants, call-centre analytics, meeting transcription and accessibility features. Accuracy varies significantly by domain; legal, medical and regional British accents often benefit from custom adaptation.
Why It Matters
Business relevance for UK organisations
UK contact centres use speech recognition to analyse 100% of calls for compliance, quality and customer intent — previously only a small sample could be reviewed manually.
Real-world example
How this shows up in practice
A Glasgow contact centre deployed speech recognition across 120,000 monthly calls, identifying a single mis-scripted sales line responsible for 18% of post-call complaints.
Related Terms
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Natural Language Processing is the field of AI concerned with interpreting, understanding and generating human language. NLP underpins chatbots, translation, summarisation, sentiment analysis, voice assistants and much of the productivity software UK teams now rely on daily.
BasicsDeep Learning
Deep Learning is a branch of machine learning that uses multi-layered neural networks to learn highly complex patterns directly from raw data such as images, audio and text, without the need for hand-crafted feature engineering.
BusinessCustomer Intelligence
Customer intelligence is the practice of combining data from every customer touchpoint and applying analytics and AI to produce a clearer picture of who customers are, what they want, and how they are likely to behave next.
AdvancedMultimodal AI
Multimodal AI refers to models that can process and generate multiple data types — text, images, audio, video — within a single system. They unlock workflows that were previously stitched together across many separate models.