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Conformer2

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Meet Conformer-2: Advanced Speech Recognition Featuring Greater Accuracy and Faster Processing

3
Speech-to-TextContact
#AI model#automatic speech recognition#Conformer-2#proper nouns#alphanumerics#noise resistance#English audio#performance improvement#Conformer-1#word error rate#latency
Inputs: audioOutputs: text
Type
Saas
Company
AssemblyAI
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Conformer2 screenshot

About Conformer2

Conformer-2 is a state-of-the-art speech recognition model developed by AssemblyAI, trained on 1.1 million hours of English audio data. It builds on Conformer-1 with significant improvements in proper nouns (6.8% error rate reduction), alphanumerics (31.7% improvement), and noise robustness (12.0% improvement), while maintaining word error rate parity. The model leverages model ensembling for pseudo-labeling and scaling laws inspired by DeepMind's Chinchilla paper. Additionally, inference latency has been reduced by up to 53.7% compared to Conformer-1, making it suitable for real-time applications. Conformer-2 is designed for real-world audio conditions and is available through AssemblyAI's API.

Key Features

31.7% improvement on alphanumerics
6.8% improvement on Proper Noun Error Rate
12.0% boost in noise robustness
Trained on 1.1M hours of English audio
Maintains word error rate parity with Conformer-1
Up to 53.7% reduction in latency
Enhanced performance in real-world audio conditions
Improved transcription accuracy
Increased number of models used for pseudo-labeling data
Developed by AssemblyAI

Pros & Cons

Pros
  • State-of-the-art speech recognition performance
  • Significant improvements on proper nouns and alphanumerics
  • Excellent noise robustness for real-world conditions
  • Reduced inference latency (up to 53.7%)
  • Uses advanced model ensembling for better accuracy
  • Maintains high accuracy while improving user-oriented metrics
Cons
  • Proprietary model only available via AssemblyAI API
  • Requires internet connection for API usage
  • Pricing requires contacting sales (no self-serve tier listed)

Best For

Podcasters: Enhance transcription accuracy for podcasts, especially with proper nouns and alphanumerics.Business professionals: Improve the transcription quality of business meetings and conferences with enhanced noise robustness.Media creators: Accurately transcribe video content, ensuring proper noun correctness and alphanumeric accuracy.Researchers: Transcribe interviews and focus group discussions with high accuracy, even in noisy environments.Customer service teams: Utilize accurate transcriptions for customer interactions, improving service quality and response time.Educational institutions: Provide precise transcriptions for online courses and lectures, accommodating proper nouns and complex alphanumerics.Journalists: Obtain reliable transcriptions of interviews and reports, maintaining the integrity of proper nouns.Healthcare providers: Accurately transcribe medical dictations and notes, supporting critical alphanumeric and proper noun recognition.Market researchers: Analyze consumer feedback and focus group recordings with high transcription accuracy in various environments.Software developers: Integrate advanced speech recognition into applications, delivering accurate transcriptions in real-time scenarios.

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