Voice and speech AI
Speech-to-text, text-to-speech, and voice assistants for hands-free workflows and accessibility.
Voice AI lets users interact without typing - ideal for hands-busy environments, accessibility, or when speed matters. Speech-to-text transcribes calls, meetings, or dictation. Text-to-speech reads content aloud or powers IVR. Voice assistants handle commands and queries.
I integrate voice AI into your products and workflows. Common use cases include transcribing customer calls for compliance, voice-controlled warehouse systems, or an IVR that understands natural language. The tech (Whisper, ElevenLabs, cloud APIs) is mature; the work is fitting it to your use case and handling accents, noise, and domain vocabulary.
Example AI integrations
AI services and tools I've integrated for businesses include:
OpenAI Whisper
Speech-to-text model for transcription and translation. For voice AI, it transcribes calls, meetings, and dictation with high accuracy.
ElevenLabs
AI voice synthesis for natural text-to-speech. For voice AI, it generates natural-sounding speech for IVR and assistants.
AssemblyAI
Speech-to-text API with summarisation and sentiment. For voice AI, it transcribes and analyses calls with summaries and sentiment.
Deepgram
Real-time speech recognition and transcription API. For voice AI, it provides real-time transcription for live conversations.
Vapi
Voice AI platform for phone and voice assistants. For voice AI, it builds phone and voice assistants with LLM backends.
Google Cloud Speech
Speech-to-text and text-to-speech APIs. For voice AI, it powers transcription and TTS for hands-free workflows.
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Types of businesses I work with
- E-commerce and retail - Product search, customer support, inventory and order triage, and personalised recommendations.
- Healthcare and life sciences - Clinical documentation, medical records, research automation, and compliance for healthcare providers.
- Logistics and supply chain - Route optimisation, demand forecasting, inventory planning, and shipment tracking with AI.
Frequently asked questions
- Modern speech-to-text models like Whisper handle regional accents well, including Yorkshire English. For specialist vocabulary or strong dialect, I fine-tune the system on sample audio from your team to improve accuracy further.
- Yes. AI transcription can record and transcribe customer calls in real time or from recordings, with speaker separation. Transcripts can be automatically flagged for compliance keywords, stored securely, and made searchable for audits.
- Yes, with the right setup. Noise-cancelling microphones and models trained on noisy audio handle industrial environments well. I test with real audio from your environment to ensure accuracy before deployment.
- Speech-to-text converts spoken audio into written text - useful for transcription and documentation. A voice assistant goes further: it understands commands, answers questions, and triggers actions. Both use speech recognition, but a voice assistant adds AI reasoning on top.
Can AI speech recognition handle Yorkshire accents?
Is voice AI suitable for recording customer calls for compliance?
Can voice AI work in noisy environments like warehouses or factories?
What is the difference between speech-to-text and a voice assistant?
Want to discuss AI for your business?
I help businesses integrate AI into their workflows. Get in touch to talk through your specific situation.