Thanaritt Kunajak

is working from home. 🏡

Bis 2024, Computational Linguist, Apple
Barcelona, Spanien

Fähigkeiten und Kenntnisse

Regex
Java
C/C++
Python
Thai language
English Language
Japanese
Deep Learning
Machine Learning
Git
CI/CD
Spanish Language
Data Science
Natural Language Processing (NLP)
latex
sublime
hugging face
Jira
Confluence
Google Sheet
Microsoft Excel

Werdegang

Berufserfahrung von Thanaritt Kunajak

  • 1 Jahr und 11 Monate, Mai 2022 - März 2024

    Computational Linguist

    Apple

    • Launched 2 new Siri voices for Thai locale to replace the old voice • Fine-tuned feature selection in a deep learning architecture’s training pipeline, resulting in enhanced model accuracy and performance through targeted evaluation and adjustments • Reviewed and debugged TTS responses to fix incorrect pronunciations, unnatural prosody, and inaccurate tonal outputs • Curated, cleaned, transformed, and analyzed text corpora using Python, regular expression, Pandas, HuggingFace, and PyThaiNLP

  • 2 Monate, März 2022 - Apr. 2022

    Production Linguist

    Apple

    • Localized, translated, and created Thai dialogue scripts based on American English originals • Created automated tools/scripts to facilitate linguist works using Python and Regular expression

  • 3 Jahre und 10 Monate, Juni 2018 - März 2022

    Assosicate Linguist

    Google

    Contractor via Pactera and Accenture • Created, annotated, and reviewed linguistic data, developed context-free grammars (CFG) used for Natural Language Understanding (NLU), and performed evaluation and error analysis for existing and new Google Assistant Conversational AI features • Reviewed linguists’ work to ensure technical integrity and design compliance of the domain • Provided onboarding training sessions to 15 new joiners; recordings are being used as part of the training curriculum

  • 3 Monate, Juni 2017 - Aug. 2017

    Data Scientist Intern

    Thomson Reuters

    • Implemented real-time anomaly detection on streaming time series data, using an unsupervised learning method called "HOT SAX" (Eamonn Keogh, 2006) to solve the issues of shortage of labelled training data and low computational resources.

  • 2 Monate, Juni 2016 - Juli 2016

    Research student

    Japan Advanced Institute of Science and Technology

    • Conducted NLP research on the topic of "Examination of Influence of Context Window Size in Word Sense Disambiguation" The task was to examine the correlation between the context window size and the accuracy of WSD. With “bag-of-words” feature vectors and the SVM algorithm as the classifier, results have shown that the optimal context window size for each word varies depending on each word’s part-of-speech category, which may result from the topicality of each POS type.

Ausbildung von Thanaritt Kunajak

  • 3 Jahre und 11 Monate, Juli 2013 - Mai 2017

    Computer Engineering

    Chulalongkorn University

    Relevant Courses: Auto Speech Recognition, Time Series Mining and Knowledge Discovery, Grammatical System, Languages in ASEAN+3

Sprachen

  • Englisch

    Fließend

  • Japanisch

    Grundlagen

  • Thai

    Muttersprache

  • Spanisch

    Gut

  • Catalan

    Grundlagen

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