Italian Language - Audio Annotation & Transcription
Pubblicato il 11-09-2026 - Zyka AI in Italia
We are looking for motivated students to join a short-term paid internship focused on Italian audio annotation and transcription. Interns will work on speech and language datasets by listening to short audio clips, transcribing spoken Italian accurately, and marking relevant audio events.
This is a great opportunity for students interested in Artificial Intelligence (AI), language technologies, speech processing, data annotation, and real-world industry projects. Prior experience is not required—training and onboarding will be provided.
Duration: 2 Weeks
Joining : Immediate
Working Hours: Flexible
Expected Commitment: 5–6 hours/day preferred
Compensation: EUR 200–300
Certificate: Provided upon successful completion
Responsibilities
- Listen to short audio segments (10–20 seconds).
- Transcribe spoken Italian accurately.
- Identify and mark pauses, background noise, overlapping speech, coughs, unclear speech, and unintelligible audio.
- Follow annotation guidelines carefully.
- Review completed work for quality and consistency.
Skills Required
- Native or near-native Italian proficiency.
- Good English reading and comprehension skills.
- High attention to detail.
- Basic computer proficiency.
- Ability to follow detailed instructions.
- No prior experience required. Training will be provided.
Ideal Candidate
- Students or recent graduates in Italy.
- Native or fluent Italian speakers with strong listening and comprehension skills.
- Interested in AI, language technologies, speech processing, or data-related work.
- Comfortable working remotely and independently.
- Careful, patient, and detail-oriented.
- Have a laptop/desktop and a stable internet connection.
Selection Process
Candidates will complete a short Italian transcription assessment before onboarding.
Application
Interested candidates may share their details and availability. Shortlisted applicants will be contacted for the transcription assessment and onboarding process.