Improving Conversational AI through Accurate Finnish Transcription

Introduction 

In the rapidly evolving world of artificial intelligence and conversational AI, accurate and high-quality voice data is crucial for the development and improvement of machine learning models. e2f, a leading company in creating data for conversational AI, embarked on a Finnish Transcription Project to convert hundreds of hours of call centre audio files into text. The objective was to enhance their conversational AI by understanding and analysing human language from diverse sectors such as banking, retail, and real estate.  

e2f entrusted myTranscriptionPlace with the challenging project of providing Finnish transcription for approximately 300 hours. To ensure timely completion, myTranscriptionPlace deployed a team of over 25 skilled transcribers, successfully accomplishing the task within just 45 days.

Project Objectives 

The primary objective of the project was to transcribe Finnish audio files with a high level of accuracy. The collaboration aimed to achieve a transcription accuracy rate of 99% for the 300 hours of call centre audio files. Given the diverse nature of the audio sources, ranging from call centre conversations to media recordings, the task posed significant challenges to the transcribers. However, with dedication and expertise, the team at myTranscriptionPlace successfully completed the project, meeting the high accuracy goal set for the transcription task. 

Transcription Challenges 

Transcribing Finnish audio content can be particularly challenging due to the unique characteristics of the Finnish language. Additionally, audio quality variations were a significant obstacle, as low-quality recordings could hamper the transcription process. The transcribers needed to be well-versed in Finnish vocabulary, dialects, and context to ensure accurate transcription. The collaboration with myTranscriptionPlace was aimed to address these challenges and deliver precise transcriptions. 

Quality Assurance 

To maintain the desired accuracy level of 99%, myTranscriptionPlace implemented a rigorous quality assurance process. Transcribed content went through multiple rounds of review, cross-checking, and proofreading to ensure precise conversion from audio to text. The quality assurance team used strict guidelines to adhere to the project's objectives and maintain consistency across the transcripts. 

Conclusion 

The collaboration between e2f and myTranscriptionPlace exemplified the critical role accurate transcription plays in the development of conversational AI. By delivering precise transcriptions from challenging Finnish audio content, myTranscriptionPlace helped e2f improve their AI models significantly. The success of the Finnish Transcription Project showcased the importance of collaboration and the expertise of transcription service providers in advancing AI technology and meeting industry demands. 

As a result of this project, e2f continued to leverage the power of conversational AI to improve various business processes. Additionally, myTranscriptionPlace's exceptional performance in providing accurate Finnish transcriptions led to a fruitful ongoing partnership, with myTranscriptionPlace collaborating on many other projects with e2f.