Support Linguist for TTS – Data, QA & Normalization

Covalen; Sandyford; Hybrid; EUR 42,000 - 56,000; Full time

Benefits offered by this job

Fully subsidised healthcare

25 days annual leave

Employee assistance programme (EAP)

PRSA Scheme

Extensive Training & Development

Annual company events

Bike to work scheme

Free parking on-site

Job summary

Covalen is seeking a detail-oriented Support Linguist for Text-to-Speech to enhance speech technologies in the candidate language. You will evaluate linguistic and audio outputs, contribute to text normalization, and identify language-specific challenges with data-driven approaches.

The role involves responsibilities before and after launch, including regression testing, dataset curation, and G2P evaluation. Collaboration and independent work are expected.

Qualifications

• Degree in Linguistics or demonstrated IPA knowledge.
• Working knowledge of Pandas for data review and manipulation.
• Regex for text processing and validation.
• Native or near-native speaker - Italian, Spanish, or Portuguese-Brazilian with fluent English (C1).
• Experience in speech/language technologies is advantageous.

Responsibilities

• Evaluate linguistic and audio quality of Text-to-Speech outputs.
• Support improvements in the TTS pipeline including text normalization and pronunciation prediction.
• Identify language-specific challenges and propose test scenarios.
• Perform data quality checks and improve linguistic datasets.
• Analyse text and linguistic datasets to identify patterns and errors.
• Use Pandas and Regex for linguistic data analysis and validation.

Skills

Linguistic knowledge

Attention to detail

Analytical thinking

Data interpretation

Communication skills

Team collaboration

Python basics

Education

Linguistics degree or IPA knowledge

Fluent English (C1)

Tools

Pandas

Regex

Python

G2P datasets

Job description

Covalen is seeking a detail-oriented Support Linguist for Text-to-Speech to enhance speech technologies in the candidate language. You will evaluate linguistic and audio outputs, contribute to text normalization, and identify language-specific challenges with data-driven approaches.

The role involves responsibilities before and after launch, including regression testing, dataset curation, and G2P evaluation. Collaboration and independent work are expected.