La question devrait être plutôt posée ainsi: Comment votre processus d’analyse linguistique, généralement, peut-il améliorer les outils d’IA ? Ces derniers ne peuvent alors que donner des résultats plus pertinents car les processus d'analyse linguistique tiennent compte des réalités humaines (sémantique, cognition, NLP en général...) contrairement à une IA qui s'appuie principalement sur des calculs qui ne tiennent pas compte de la complexité du cerveau humain. Principalement, en matière de résumé de texte automatique, une IA ne pourra jamais donner de meilleurs résultats qu'un système qui tient compte de la linguistique appliquée.

AI tools enhance transcription accuracy and linguistic analysis by automating tasks and using speech-to-text software to convert audio to text quickly and accurately. Language-specific AI models improve transcription by recognizing local accents and dialects, while real-time error detection identifies inconsistencies early. AI tools integrate multimodal analysis, correlating audio, video, and text for richer insights. They can also automatically tag linguistic features like parts of speech and syntax, streamlining analysis. Customizable AI models improve accuracy for niche languages, and AI helps organize large datasets, making data more searchable and accessible for deeper, more efficient linguistic analysis.

AI tools improve transcription accuracy by: 1. Automatic Transcription NLP, an AI domain for text and audio processing can convert audio to text or vice versa, reducing human errors. Developments in NLP have recognized accents, dialects, abbreviations, jargon, and emotions, thereby improving accuracy even in noisy environments or with unclear speech. 2. Error Detection and Correction LLM is an advanced NLP model that can automatically identify and correct transcription errors. LLM learns from large datasets and uses contextual understanding to flag potential errors in grammar, and semantics, and suggest corrections, making it effective in handling complex language patterns and idiomatic expressions that are prone to transcription errors.

AI-powered transcription tools like Otter.ai, Rev, or Descript can transcribe audio files with impressive accuracy, reducing manual effort. These tools are trained to recognize speech patterns and language nuances, providing a strong starting point for your analysis.