SquadStack Launches Arth V2 Speech Model for Indian-Language Calls
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 the company's own benchmark and have not been independently verified.
The Noida-based company said Arth V2 has processed more than one crore minutes of live customer calls over two months. The model is deployed within SquadStack's voice AI agents for enterprise customers and is also available in closed...
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