Turn Khmer audio
в текст, которому можно доверять.

A different approach to Khmer transcription.

Khmer is the official language of Cambodia, spoken by more than 16 million people, with communities across Thailand, Vietnam, and the diaspora worldwide. Unlike Thai or Vietnamese, Khmer is non-tonal, meaning comes from context and word order rather than pitch, but it carries one of the longest alphabets still in use, 74 characters, plus stacked subscript consonants and centuries of Sanskrit and Pali loanwords inherited from the Khmer Empire and Angkor Wat. Turning Khmer speech into usable text has always meant either a bilingual transcriber working by hand, or software tuned for higher-resource languages that gets the words roughly right and drops everything else.

Where Khmer transcription usually breaks down

Most transcription tools are tuned for a handful of high-resource languages, and Khmer rarely gets the same attention. Speakers get misheard, technical or regional terms get flattened into nonsense, and tone, hesitation, or emphasis in the recording never make it into the transcript at all. Teams end up correcting entire passages by hand, which erases most of the time an automated tool was supposed to save.

Анализ записи, а не просто слов

Speak AI transcribes Khmer audio and video with speaker labels and timestamps, then reads the recording itself: who is speaking, when they switch between Khmer and English mid-sentence, and how the delivery changes across a long interview or hearing. Names, terms, and callback details are extracted into structured fields your team can search and query. Then you can ask across your entire Khmer archive with AI chat, using ChatGPT, Claude, and Gemini built directly into the workspace.

• Khmer audio and video, transcribed directly into Khmer script with speaker labels and translation into English or another language.
• Handles Sanskrit and Pali loanwords and stacked subscript consonants that generic transcription tools tend to flatten or drop.
• Captions and subtitles (SRT, VTT) generated straight from the timestamped transcript.
• Export to Word, PDF, TXT, CSV, or JSON, depending on how your team needs to use it.

Из одного файла в доступный для поиска архив

The result is a Khmer archive that behaves like a well-run English one. Interviews, hearings, and support calls become searchable text instead of a folder of audio files nobody has time to relisten to, and панели, которые вы можете настраивать и белой этикеткой track themes and volume across your Khmer recordings over time. Interpreting.com put its multilingual assessment recordings through this kind of workflow, scaling embedded recorders across dozens of languages including Khmer, without hiring a reviewer for each one.

And because Khmer recordings rarely live in isolation from the rest of your work, the same engine scores calls and coaches teams on the same criteria, connecting Khmer transcription to оценка звонков and the wider база знаний your team already runs on.