What Is Speech-to-Text? Practical Uses at Work

Speech-to-text (also called speech recognition or voice-to-text) is technology that converts spoken words into written text. You speak, and the software produces a text transcription. Every time you dictate a message on your phone or ask a voice assistant a question, speech-to-text is doing the conversion.

How speech-to-text works

The process starts when a microphone captures your voice as an audio signal. The software then breaks that audio into tiny segments, typically a few milliseconds each. Each segment is analysed to identify the sounds (called phonemes) being produced.

Older speech-to-text systems matched these sounds against a fixed dictionary of words. Modern systems use AI models trained on thousands of hours of recorded speech. These models predict not just individual words but entire phrases, using context to choose between words that sound identical. For example, the model uses surrounding words to determine whether you said "their," "there," or "they're."

The accuracy of modern speech-to-text is remarkably high for clear, well-paced speech in supported languages. English recognition regularly exceeds nearly all accuracy in good conditions. Background noise, strong accents, and unsupported languages reduce that number.

Practical uses at work in Kenya

Meeting transcription. Instead of taking notes during a client meeting, you record the session and run it through a speech-to-text tool. Otter.ai, Google's recorder app, and Whisper (an open-source model by OpenAI) all produce transcriptions within minutes. This is practical for consultants, project managers, and anyone who needs accurate meeting records without hiring a dedicated note-taker.

Dictating reports and emails. On a Nairobi commute, typing a long email on your phone is frustrating. Dictating it is faster. Google's voice typing (available on Gboard) and Apple's dictation feature convert your speech into text directly in any app. For professionals who process high volumes of correspondence, this can save an hour or more per day.

Customer service documentation. Call centres and customer-facing businesses use speech-to-text to transcribe phone calls automatically. If you run a support operation, transcribed calls create searchable records, making it easy to review past interactions without listening to hours of recordings.

Accessibility. Speech-to-text makes digital tools usable for people who cannot type easily due to physical limitations, visual impairment, or situations where their hands are occupied. In a country where smartphone usage outpaces laptop ownership, voice input is often the most natural interface.

Content creation. Writers, bloggers, and social media managers often dictate first drafts rather than typing them. Speaking produces a more conversational tone and is typically three to four times faster than typing. The transcript serves as a rough draft that you then edit into polished content.

Language support and the Kenyan context

English speech-to-text works reliably with Kenyan-accented English, though some tools perform better than others. Google's speech recognition handles East African English accents well because its training data includes diverse English speakers. Apple's Siri and Whisper also perform adequately.

Swahili support exists but varies. Google Translate's voice input supports Swahili, as does Gboard's voice typing. Accuracy for Swahili is lower than English because training data is more limited. Code-switching between English and Swahili in the same sentence (common in Kenyan workplaces) can confuse most tools, often producing garbled output at the switch points.

Other Kenyan languages (Kikuyu, Luo, Kalenjin, Luhya) have minimal speech-to-text support in commercial tools. Open-source projects are making progress, but production-ready recognition for these languages remains limited.

Tips for better accuracy

Speak at a natural pace. Rushing or speaking unnaturally slowly both reduce accuracy. Pause briefly between sentences rather than running everything together. Use a decent microphone; your phone's built-in mic works in quiet settings, but a simple lapel mic improves results in noisy environments. Reduce background noise when possible, as keyboards, traffic, and office chatter all interfere.

The output always requires proofreading. Even at nearly all accuracy, a five-minute recording can contain dozens of small errors: misheard words, missing punctuation, or incorrect proper nouns. Treat speech-to-text output as a draft, not a final version.

We cover speech-to-text alongside other core AI terms in our glossary. Related concepts include tokens (how AI measures text length) and hallucination (when AI generates incorrect output).

FAQ

Is speech-to-text free?

Yes, for basic use. Google's voice typing on Android, Apple's dictation, and the free tier of Otter.ai all offer speech-to-text at no cost. Paid plans add features like longer recordings, speaker identification, and API access for automation.

Can speech-to-text handle Sheng?

Not reliably. Sheng blends Swahili, English, and other languages in ways that current models are not trained to handle. The tool will attempt to match sounds to its known vocabulary, producing inconsistent results. For Sheng content, manual transcription or heavy editing of the automated output is still necessary.

How long can a recording be?

It depends on the tool. Google's voice typing works in real time without a set limit. Otter.ai's free plan allows recordings up to 30 minutes. Whisper can process files of any length but requires a computer to run. For very long recordings (multi-hour seminars), splitting the file into shorter segments usually improves accuracy.