Turn Pashto audio
into words that hold up.

A different approach to Pashto transcription.

Pashto transcription is the process of converting spoken Pashto, an interview, a call, a field recording, into accurate written text using AI speech recognition tuned for the language. Pashto is an Indo-Iranian language spoken by more than 50 million people, official in Afghanistan and widely spoken across Pakistan’s Pashtun regions, with diaspora communities in Iran, the Gulf states, the United States, the United Kingdom, and Canada. It carries a deep poetic tradition and a range of regional dialects, some distinct enough that speakers of different dialects can struggle to understand each other.

Why Pashto audio stalls in a queue

Most transcription software is tuned for a handful of major languages and treats everything else as an afterthought. Pashto makes that worse in two ways: its dialects vary enough that a model trained on one region can misread another, and its Perso-Arabic script, written right to left with letters that change shape depending on position, trips up tools built around Latin alphabets. The result for most teams is a manual backlog: files that sit until someone who speaks the dialect has time to listen and type.

理解信息的含义，而不仅仅是词语

Speak AI transcribes Pashto natively, with 100+ languages supported overall, and reads across its dialects rather than assuming one region speaks for all. Alongside the words, the recording itself is analyzed: tone, energy, and sentiment, tracked the same way whether the speaker is on their fifth interview of the day or their first call with a new contact. Names, terms, and the fields your team actually needs are extracted automatically, and the same layer connects into Claude, ChatGPT, and Cursor through the MCP server, so you can ask questions across every Pashto file without opening each one.

What teams ask their Pashto transcripts

• “Pull every mention of pricing across this month’s Pashto client calls.”
• “Which interviews switched from Pashto into Dari or English, and where?”
• “Summarize the main themes across these 30 Pashto intake interviews.”
• “Export this Pashto transcript as SRT captions for the video team.”

From a manual backlog to a searchable archive

The result is a Pashto transcription workflow that keeps up with how the language is actually spoken, dialect shifts included. Terms and themes across hundreds of files become 可自定义和白标的仪表板, tracking usage and sentiment over time instead of a folder of one-off documents. An education group running multilingual assessments across several languages put its recordings through this same workflow and scaled it with Interpreting.com 多语言 embedded recorders, without adding headcount to review the backlog by hand.