Focus Group Audio Transcription Built for Overlapping Speech
Focus group discussions (FGDs) are notoriously hard to transcribe: people interrupt, talk over each other, and shift between languages. Andebet's neural diarization isolates distinct voices and maps every participant's argument with timestamped precision.
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Microfinance Community Focus Group (Hawassa)
Amharic & Sidama-accented Dialogue • 03:10
የብድር ክፍያ ሂደቱ ላይ ያጋጠማችሁን ዋነኛ ተግዳሮት በግልጽ ብትነግሩን? ወለዱ ወይስ የክፍያ ጊዜው?
“Could you tell us openly the main challenge you faced in the loan repayment process? Was it the interest or the repayment schedule?”
የክፍያ ጊዜው በጣም አጭር ነው። ምርቱ ሳይሸጥ ሳምንታዊ ክፍያ መጀመሩ በንግዱ ላይ ጫና ይፈጥራል።
“The repayment schedule is too short. Starting weekly repayments before the harvest sells creates severe pressure on the business.”
ትክክል ነው! እኔም የምስማማው እዛ ላይ ነው። አበዳሪው ተቋም የግብርና ወቅቱን ከግምት ውስጥ ማስገባት አለበት።
“Exactly! I agree with that completely. The lending institution needs to take agricultural seasons into account.”
Engineered for the Chaos of Multi-Party Group Audio
While standard transcription models stumble when multiple people speak simultaneously, Andebet was trained specifically on multi-microphone and roundtable discussions.
Overlapping Speech Handling
Our acoustic segmentation model detects overlapping speech turns and separates conversational crosstalk into distinct participant lines.
Speaker Cluster Identification
Assigns consistent speaker identities throughout a 2-hour discussion, even when participants laugh, pause, or change pitch.
Participant Quote Extraction
Highlight and tag key participant quotes with one click. Export categorized excerpts with exact speaker names and audio timestamps.
Multi-Language Discussions
Handles group discussions where participants alternate between Amharic, Afaan Oromo, and English naturally during heated debates.
From Multi-Hour FGD to Grounded Synthesis
How qualitative researchers turn complex focus group recordings into actionable insights.
Upload Group Audio or Video
Upload room recordings from boundary microphones, smartphones placed in the center of the table, or Zoom gallery recordings.
Supports omni & multi-channel audio
Cluster-Based Speaker Separation
Our neural model profiles each voice in the room, generates acoustic embeddings, and splits the audio stream into distinct participant tracks.
Labels Speaker 1 through Speaker 8+
Assign Participant Names & Roles
Quickly map 'Speaker 1' to 'Moderator', 'Speaker 2' to 'Farmer Rep (Abebe)', etc. Colors and labels update instantly across the entire transcript.
One-click participant rename
Thematic Coding & Synthesis
Ask conversational questions across your focus groups using Corpus Analysis or export to Word and ATLAS.ti for thematic qualitative coding.
Export with speaker & time metadata
Who Uses Andebet for Focus Group Transcription?
Trusted by market researchers, social scientists, and monitoring & evaluation specialists.
Market & Consumer Researchers
Market research agencies, consumer brand strategistsTranscribe consumer focus groups to understand customer sentiments, price sensitivity, and packaging feedback across Ethiopia.
Public Health Evaluators
WHO partners, health ministries, epidemiological researchersDocument community health dialogues, vaccination hesitation discussions, and patient focus groups with verbatim accuracy.
Social & Development Economists
World Bank contractors, academic think tanks, NGOsExtract nuanced qualitative evidence from beneficiary groups regarding safety net programs, cash transfers, and climate resilience.
Policy & Civic Engagement Teams
Governance initiatives, municipal councils, civic coalitionsTranscribe town hall sessions and citizen focus groups to synthesize community priorities for regional government reporting.
Frequently Asked Questions: Focus Group Transcription
Technical details on participant limits, microphone setup, and overlapping speech.
Andebet reliably separates up to 10 to 12 distinct voices in a single recording. For optimal results, ensure participants speak clearly towards the microphone and avoid heavy physical table tapping.
Andebet's acoustic segmentation model detects overlapping speech bursts. Instead of dropping words or hallucinating text, it transcribes the primary voice and segments the interrupting turn with overlapping timestamp markers.
Yes! You can filter the transcript by specific speaker names to view only what that person said, or use keyword search to find every instance where a particular topic was raised by any participant.
Yes. Our exported Word (.docx) and plain text (.txt) files adhere to standard qualitative research formatting (e.g. 'Speaker Name: [Timestamp] Transcript text'), making them immediately importable into NVivo, ATLAS.ti, and MAXQDA.
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LanguageAmharic Audio Transcription
Native Ge'ez fidel speech recognition with built-in diarization.
Turn recorded Ethiopian conversations into searchable truth.
Join researchers, media networks, and global organizations extracting structured knowledge from Amharic, Afaan Oromo, and Tigrinya audio.
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