Native Japanese Speaker for Audio & Transcript Quality Labeling

Remote Full-time
We are seeking highly meticulous and detail-oriented Native Japanese Speakers for a data quality labeling project. This project is crucial for improving Japanese speech recognition and AI language models.

Your role will be to listen to Japanese audio clips, review their corresponding transcripts, and provide a detailed quality assessment based on a clear set of instructions. This is more than a simple transcription job; it requires a deep understanding of Japanese linguistic nuances, including kanji and homophones.

Responsibilities:

Your primary task will be to evaluate audio-transcript pairs by completing a guided questionnaire for each pair. This involves:

Language Verification: Confirming that both the audio and transcript are in Japanese.

Audio Quality Assessment:

Evaluating the clarity and quality of the audio.

Identifying the number of speakers in the clip.

Detecting any overlapping speech (when people talk at the same time).

Transcript Accuracy Analysis:

Comparing the transcript to the audio to ensure it is 100% accurate, with no missing, extra, or incorrect words.

If errors are found, you will be required to provide the complete, corrected transcript.

Japanese-Specific Linguistic Error Identification:

Kanji Ambiguity: Identifying and counting instances where the wrong kanji is used for a word, despite having the same or a similar reading (e.g., 橋 vs. 箸).

Homophone Errors: Identifying and counting mistakes where words that sound the same but have different meanings are confused (e.g., 海 vs. 産み).

Providing detailed, formatted comments explaining these specific errors.

Requirements:

Native-level fluency in Japanese (listening, reading, and writing) is mandatory.

A strong, nuanced understanding of Japanese grammar, vocabulary, kanji, and homophones.

Exceptional attention to detail and the ability to spot subtle errors.

Ability to follow complex instructions precisely and work independently.

A reliable internet connection and access to good quality headphones are required.

Previous experience in transcription, translation, proofreading, or data labeling is a strong plus.

Experience working with data annotation tools is preferred but not required.

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