In Quebec and Canadian courts, the transcription of court proceedings is a critical task for appeal purposes and must be certified by an official court reporter. The limited availability of qualified reporters and the high costs associated with manual transcription underscore the need for more efficient solutions. This paper examines the potential of Automatic Speech Recognition (ASR) systems to assist court reporters in transcribing legal proceedings. We benchmark three ASR models, including commercial and open-source options, on their ability to recognize French legal speech using a curated dataset. Our study evaluates the performance of these systems using the Word Error Rate (WER) metric and introduces the Sonnex Distance to account for phonetic accuracy. We also explore the broader implications of ASR adoption on court reporters, copyists, the legal system, and litigants, identifying both positive and negative impacts. The findings suggest that while current ASR systems show promise, they require further refinement to meet the specific needs of the legal domain.

Tech Insider recently published an article about the first artificially intelligent lawyer. ROSS – the name of the artificial intelligence (AI) – can search court rulings from 13 years ago, along with opinions about the case at hand and its significance to past court verdicts. ROSS also sifts through all of this information and provides the user with only highly relevant data. ROSS even operates in plain language, which is a huge step in artificial intelligence, as current systems search and process data in list form, which is not how court rulings and cases are documented. ROSS was recently'hired' at a bankruptcy firm, and several other firms have requested the AI lawyer as well.