Speech to Text: How Audio Transcription Works

Speech-to-text is a technology that converts spoken words in an audio recording into a written text transcript. The software listens to the audio, identifies phonemes (the smallest units of sound in a language), and maps them to words using statistical models trained on large collections of speech and text data.

The terms speech-to-text, audio transcription, voice-to-text, and automatic speech recognition are all used to describe the same core process. The result is a text file that represents what was said in the original recording — sometimes with timestamps that show when each word was spoken.

Modern speech-to-text systems use neural networks trained on hundreds of thousands of hours of audio paired with text transcripts. When you submit an audio file, the software converts the audio waveform into a spectrogram — a visual representation of how sound frequencies change over time — and passes it through a transformer model that predicts the most likely sequence of words.

Konthora uses the Whisper speech recognition model — an open-source neural network developed by OpenAI and trained on 680,000 hours of multilingual audio. Konthora specifically uses the small.en variant, which is optimised for English and runs entirely on Konthora’s servers with no data sent to third-party AI services.

The three steps that happen when you transcribe audio on Konthora are:

1. 1Your file is securely uploaded and validated.
2. 2FFmpeg extracts and normalises the audio to a 16 kHz mono WAV — the format Whisper expects.
3. 3Whisper processes the audio and returns a transcript with word-level timing data, which Konthora then groups into the timestamp mode you selected.

Speech-to-text is used wherever someone needs a written record of spoken content. The most common use cases fall into three audiences.

Free speech-to-text tools typically use open-source models such as Whisper and are suitable for individual files and occasional use. Paid services usually offer faster processing, higher file limits, batch transcription, speaker diarization, and API access — features designed for teams or high-volume workflows.

Konthora is a free, browser-based tool with no account or subscription required. It is designed for individual files up to 100 MB and 10 minutes in duration. It does not offer speaker identification, real-time transcription, or batch processing. If your workflow requires those features, you will need a paid service.

What Konthora does offer that most free tools do not: three timestamp modes (sentence, paragraph, word), four export formats (TXT, SRT, VTT, JSON), and automatic file deletion after 60 minutes — so your audio is never stored permanently.

No speech-to-text tool is perfectly accurate. Accuracy varies based on:

• Audio quality — clear, close-microphone recordings transcribe more accurately than distant or compressed audio.
• Background noise — music, echo, or crowd noise reduces accuracy.
• Speaking style — clear, moderate-pace speech transcribes more accurately than very fast speech or heavy mumbling.
• Accent — Whisper handles a wide range of English accents but performs best on standard American and British English.
• Technical vocabulary — specialist terms in medicine, law, or engineering may be transcribed incorrectly if they are rare in the training data.

For the best results with Konthora, use a clean MP3 or WAV recording with one speaker at a time, recorded at normal speaking pace in a quiet environment.