New Delhi, Oct. 12 -- SquadStack.ai has launched Arth V2, a speech-to-text model designed for Indian-language customer calls, as the company seeks to reduce transcription errors in voice-based artificial intelligence (AI) systems used for sales and customer interactions.

The company said Arth V2 recorded a semantic word error rate of 8.85% and a latency of 67 milliseconds on its internal Conversational Streaming Automatic Speech Recognition (ASR) Benchmark, which uses 863 real Indian sales calls recorded over 8 kHz telephone audio.

According to SquadStack, the model produced fewer meaning-changing transcription errors than several competing systems, including models from Sarvam, Google, OpenAI and ElevenLabs. These results are based on ...