Remote Italian QA & Transcription Specialist

The Ai Training Company; Italia; Remoto; EUR 25.000 - 55.000; Tempo pieno

Vantaggi offerti da questo lavoro

Remote work

Descrizione del lavoro

The Ai Training Company invites Italian Language Experts to join a remote AI project focused on reviewing and improving Italian transcripts, annotations, and metadata. You will listen to audio, correct machine transcripts, and ensure outputs reflect natural Italian usage.

Responsibilities include identifying transcription errors, annotating data with structured labels, and providing clear explanations of linguistic issues while upholding high quality across large datasets.

Competenze

• Good proficiency in Italian
• Experience with transcription, translation, editing, localization, linguistic review, annotation, or another language-focused discipline
• Ability to interpret spoken Italian
• Strong understanding of Italian grammar, spelling, punctuation, and linguistic conventions

Mansioni

• Review and correct machine-generated Italian transcriptions
• Compare transcripts against original audio for accuracy
• Identify missing, added, or incorrectly transcribed words
• Correct spelling, grammar, punctuation, and segmentation
• Annotate audio and transcripts using structured project guidelines
• Add metadata tags to support speech and language datasets
• Identify speakers, speech characteristics, and audio events where required
• Flag ambiguous or low-quality audio

Conoscenze

Italian proficiency

Transcription experience

Linguistic analysis

Attention to detail

Strumenti

Transcription software

Annotation tools

Descrizione del lavoro

The Ai Training Company invites Italian Language Experts to join a remote AI project focused on reviewing and improving Italian transcripts, annotations, and metadata. You will listen to audio, correct machine transcripts, and ensure outputs reflect natural Italian usage.

Responsibilities include identifying transcription errors, annotating data with structured labels, and providing clear explanations of linguistic issues while upholding high quality across large datasets.