The Learning Curve, Part 2: How to Build an AI for Diverse Dialects

Crafting an AI Masterpiece: Navigating the Complexity of Arabic Dialects

Samsung Gulf Electronics has embarked on a groundbreaking journey to bring the Arabic language in all its diversity to Galaxy AI, breaking down barriers and fostering global communication. This second installment of our Learning Curve series delves into the challenges and triumphs of developing AI capable of understanding and responding to a myriad of Arabic dialects.

Unveiling the Complexity

Arabic, one of the world’s most widely spoken languages, is rich in its diversity with over 30 distinct dialects spread across 20 countries. While Modern Standard Arabic (Fus’ha) is used in formal settings, the dialects (Ammiya) dominate everyday conversations, each with unique pronunciation, vocabulary, and grammar. Tackling this complexity required Samsung’s R&D Institute in Jordan (SRJO) to innovate and adapt.

The SRJO team, led by Mohammad Hamdan, faced the monumental task of creating an AI model that could navigate these dialectal differences. Their approach involved intricate techniques to capture and process the nuances of each dialect, ensuring accurate and contextually appropriate AI responses. “Our goal is to develop a model that understands all these dialects and can answer in standard Arabic,” Hamdan explains.

Breaking Down Barriers

The challenge of integrating Arabic into AI is multifaceted. Unlike other languages, Arabic’s phonetic and grammatical structure changes based on context. For example, the pronunciation of an object can vary depending on the subject and verb in the sentence. This complexity necessitated a highly adaptive AI model capable of discerning and applying these variations accurately.

One unique challenge was handling Arabic diacritics, essential for pronunciation but often absent in everyday text. This made converting raw text into phonemes challenging. Haweeleh and his team designed a neural model to predict and restore these missing diacritics with high accuracy, enhancing the model’s ability to generate correct pronunciations.

Building a Robust Dataset

Collecting diverse audio recordings and transcribing them was crucial for the Automatic Speech Recognition (ASR) process. Ayah Hasan’s team of native speakers meticulously converted spoken dialects into text, capturing the linguistic variety essential for ASR. “Building an ASR system that supports multiple dialects in a single model is a complex undertaking,” says Hamdan. It required careful data selection and advanced modeling techniques.

The SRJO team also had to collect diverse audio recordings of the dialects from various sources, which had to be transcribed, focusing on unique sounds, words, and phrases. “We assembled a team of native speakers in the dialects who were well-versed in the nuances and variations,” says Ayah Hasan, whose team was responsible for database creation. “They listened to the recordings and manually converted the spoken words into text.”

This work was crucial for enhancing the ASR process so that Galaxy AI could handle the rich tapestry of Arabic dialects. ASR is pivotal in enabling Galaxy AI’s real-time understanding and response capabilities.

The Culmination of Innovation

After extensive planning, development, and testing, Arabic was successfully integrated into Galaxy AI, making it accessible to millions of Arabic speakers. This achievement not only enhances communication across borders but also sets a precedent for future language integration projects. The team continues to refine their models, pushing the boundaries of what AI can achieve.

Enhancing Understanding

Neural models work similarly to human brains. To predict diacritics, a model needs to study lots of Arabic text, learn the language’s rules, and understand how words are used in different contexts. For instance, the pronunciation of a word can vary greatly depending on the action or gender it describes. Extensive training from the team was the key to enhancing the Arabic TTS model’s accuracy.

Looking Ahead

In the next episode, we’ll explore how language data is refined in Vietnam and what it takes to train an effective AI model. Arabic is just one of the many languages now supported by Galaxy AI, available for download via the Settings app on devices running Samsung’s One UI 6.1 update.

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