Turn thesis interviews into coded text faster
A master's student records interviews and focus groups, then uses automatic speaker labels to turn long recordings into readable transcripts. Across SozAI, 99% of transcripts include speaker labels.
In short
A master's student records interviews and focus groups on an iPhone or Android device, uploads each audio or video file to SozAI, and receives text with automatic speaker labels. SozAI processes a 50-minute recording in about five minutes. The student reviews speaker attribution, checks key passages, and exports the transcript as TXT, DOCX, PDF, SRT, or VTT for qualitative coding.
The setup
- Who
- Master's student conducting thesis interviews and focus groups
- Typical recording
- One-to-one interviews and multi-speaker focus groups
- Volume
- Files up to 500 MB and about 2.8 hours
- Languages
- 100+ supported; 20+ represented in usage
- Devices
- iPhone, Android, macOS, or website
- Export used
- DOCX or TXT for qualitative coding
- Storage
- EU data centers; AES-256 encryption at rest
The numbers come from anonymized aggregates from SozAI production usage and the public transcript library, not one named organisation.
Manual transcription delays coding
For thesis research, the work continues after each interview. A master’s student may record one-to-one interviews and focus groups with overlapping responses, follow-up questions, and several speakers in the room.
Before analysis begins, every recording must be reviewed, transcribed, and attributed. Manual typing and repeated listening slow coding, theme development, and supervisor review.
This composite reflects anonymized usage patterns from real SozAI production activity. It represents researchers who need transcripts they can read, highlight, and move into a qualitative analysis process.
They also need support for long recordings, clear separation between speakers, and exports that fit an existing coding workflow.
The constraints researchers face
From recording to coding-ready text
The student uploads each interview or focus-group recording to SozAI from an iPhone or Android device. The app converts audio or video to text and separates speakers automatically, helping distinguish a moderator from several respondents.
The student reviews key passages, then exports the transcript for qualitative coding. The same process supports multilingual projects across the 20+ languages represented in SozAI usage.
With the conversation organized by speaker, the student can move from raw recordings to theme tagging, answer comparison, and thesis evidence with less manual transcription.
A practical research workflow
- 1 Record a thesis interview or focus group on a phone, or capture it as video.
- 2 Upload the file to SozAI for transcription with automatic speaker labels.
- 3 Review key passages and check moderator and respondent sections.
- 4 Export the text and bring it into the qualitative coding process.
Less time between recording and analysis
The research method stays the same. The student reaches usable text sooner, so coding and writing can begin without waiting on a fully manual transcript.
A faster first pass
The student scans, annotates, and organizes a transcript instead of repeatedly listening while typing.
Clearer attribution
Automatic speaker labels help separate moderator prompts from participant responses in interviews and focus groups.
A direct path to coding
The student exports usable text and moves it into the qualitative analysis process.
What supported the workflow
Speaker labels for research conversations
With 99% of transcripts including speaker labels, SozAI fits interviews and focus groups where attribution matters.
Support for long sessions
SozAI processes files up to 2.8 hours, covering extended interviews, workshops, and group discussions.
Coverage across languages
SozAI has processed content in 20+ languages, supporting multilingual academic research.
How long each step takes
- Record the sessionUp to about 2.8 hours per file
The student records an interview or focus group as audio or video on an iPhone or Android device. Each uploaded file can be up to 500 MB.
- Upload and transcribeAbout five minutes for a 50-minute recording
SozAI converts the recording to text at about 10x real-time speed. Automatic language detection selects from the 100+ supported languages.
- Review speaker sectionsAfter processing
The student checks moderator and respondent passages, especially where focus-group speakers overlap. Automatic diarization provides speaker labels in 99% of transcripts produced in the app.
- Export for codingAfter review
The student exports the reviewed transcript as TXT, DOCX, PDF, SRT, or VTT. Word-level timestamps are included in the exported transcript formats that support them.
What this workflow does not do
Overlapping speech lowers accuracy
SozAI does not reliably resolve every overlapping response in a focus group. Word accuracy falls when speakers talk over one another, use heavy accents, record with background noise, or use phone-quality audio.
Speaker labels are not participant identities
SozAI does not know a participant's name from the recording alone. Speaker labels separate voices, but the student must verify which label belongs to the moderator or each respondent.
Human review remains necessary
SozAI does not replace checking research evidence against the recording. The student must review quotations, unclear passages, speaker attribution, and sections affected by poor audio before coding or citing them.
SozAI does not perform qualitative coding
SozAI produces the transcript and its exports; it does not assign research codes, develop themes, or replace the student's qualitative analysis process.
Terms used on this page
- Diarization
- Diarization is the automatic separation of a transcript into labeled speaker sections.
- Speaker label
- A speaker label marks which detected voice produced a passage without necessarily identifying the person's name.
- Word-level timestamp
- A word-level timestamp records the position of an individual word in the source recording.
- SRT and VTT
- SRT and VTT are timed subtitle export formats that pair transcript text with positions in an audio or video file.
A pattern across research use
This composite case reflects anonymized usage patterns across 5,400+ users. Researchers use SozAI to turn recorded conversations into text they can read, code, and cite.
The practical benefit is straightforward: less time typing recordings and more time spent on analysis, writing, and review.
Answers
Questions about this workflow
How does SozAI transcribe thesis interviews?
SozAI transcribes an uploaded audio or video recording and returns readable text with automatic speaker labels. A master's student can record on an iPhone or Android device, upload the file, review moderator and respondent sections, and export the result as TXT, DOCX, PDF, SRT, or VTT for qualitative coding.
Can SozAI separate speakers in a focus group?
SozAI provides automatic diarization, which separates detected voices into speaker labels. Across SozAI, 99% of transcripts produced in the app include speaker labels. The student still needs to check labels against the recording because overlapping speech, background noise, heavy accents, and phone-quality audio reduce word accuracy and can affect attribution.
How long does SozAI take to transcribe a 50-minute interview?
SozAI runs at about 10x faster than real time, so a 50-minute recording is typically ready in about five minutes. Processing time does not remove the need for review: the student should check unclear words, overlapping responses, speaker attribution, and quotations before using the transcript in thesis analysis.
What file size and recording length can SozAI handle?
SozAI accepts files up to 500 MB and up to about 2.8 hours per file. The student can submit an interview or focus-group recording within those limits as audio or video, then receive a transcript with speaker labels when diarization is available for the recording.
Which SozAI export should I use for qualitative coding?
SozAI exports transcripts as TXT, DOCX, PDF, SRT, and VTT. TXT or DOCX provides editable text for highlighting and coding, while SRT and VTT preserve timed subtitle structure. SozAI also provides word-level timestamps, allowing the student to locate transcript passages in the source recording.
Does SozAI support multilingual thesis interviews?
SozAI supports 100+ languages and includes automatic language detection. More than 20 languages appear in real SozAI usage, so a student can use the same transcription workflow across multilingual interviews or focus groups. Accuracy still depends on recording quality, accent, background noise, and overlapping speech.
Start transcribing your research interviews
Upload a thesis interview or focus group and get speaker-labeled text you can review and export.
