German Austria Audio Transcriber – Remote, Flexible Hours

OneForma; Deutschland; A distancia; EUR 17.000 - 24.000; Jornada completa

Descripción de la vacante

OneForma invites you to join the Freya Project—Remote Podcast Transcription and Speech Annotation. This fully remote role lets you work from home on flexible batches while contributing to voice recognition research.

Ideal candidates have strong listening skills, transcription experience, and native or near-native German (Austria) fluency. You will transcribe long-form podcasts, label speakers, timestamp segments, and help maintain high quality standards.

Formación

• Strong listening skills and attention to detail.
• Previous transcription or speech annotation experience.
• Native or near-native fluency in German (Austria) locales.
• Access to a computer and stable internet connection.

Responsabilidades

• Transcribe long-form podcast recordings accurately, following project guidelines.
• Identify different speakers and assign consistent speaker labels.
• Segment speech with accurate timestamps.
• Identify the perceived gender of speakers.
• Review audio quality and flag issues such as unclear or distorted speech, strong accents, incorrect language, and synthetic or generated audio.
• Verify and correct pre-annotated speech segments when required.
• Ensure all annotations and transcripts meet quality standards.

Conocimientos

Transcription

Speech annotation

German (Austrian)

Attention to detail

Descripción del empleo

Good with detail? Turn it into flexible remote work

Join our Freya Project: Remote Podcast Transcription and Speech Annotation

OneForma is hiring remote transcription and speech annotation specialists for a long-form audio project. In this role you will transcribe and annotate podcast recordings to help train and evaluate voice recognition models. If you have strong listening skills, excellent attention to detail, and transcription experience, we would love to hear from you.

About the Project

This project focuses on accurately segmenting and transcribing speech within long-form audio recordings. Your work directly supports the training and evaluation of voice recognition and speech-to-text models across a wide range of languages and locales.

Purpose of the Project

The goal of this project is to accurately segment and transcribe speech within long-form audio recordings in order to train and evaluate voice recognition models.

Task Description

In this role you will analyze long-form podcast recordings of 30 to 60 minutes or more and perform high-quality transcription and speech annotation tasks following detailed project guidelines.

Key Responsibilities

• Transcribe long-form podcast recordings accurately, following project guidelines.
• Identify different speakers and assign consistent speaker labels.
• Segment speech with accurate timestamps.
• Identify the perceived gender of speakers.
• Review audio quality and flag issues such as unclear or distorted speech, strong accents, incorrect language, and synthetic or generated audio.
• Verify and correct pre-annotated speech segments when required.
• Ensure all annotations and transcripts meet quality standards.

What We Are Looking For

• Strong listening skills and excellent attention to detail.
• Previous experience with transcription or speech annotation.
• Native or near-native fluency in German Austria target languages and locales.
• Access to a computer and a stable internet connection.

Location

This is a fully remote opportunity. You can complete all tasks from home on your own schedule, within the availability windows for each batch.

Payment

• Earn €15.12 per hour and up to €120 per day.
• Earnings are calculated from billable time only, which is automatically tracked on the task platform
• Work as much as you want up to 10 billable hours per day.
• Tasks are released weekly on a first-come, first-served basis. Volume varies by week

Availability and Task Duration

Tasks are released weekly on a first-come, first-served basis. Volume may vary depending on your locale and batch distribution.