궁극의 가이드 - 2026년 콜센터를 위한 최고의 소형 AI 모델

What are Small AI Models for Call Centers?

Small AI models for call centers are compact, efficient text-to-speech (TTS) systems designed to convert text into natural-sounding speech for customer service applications. Using advanced deep learning architectures with optimized parameter counts, these models deliver high-quality voice synthesis with low latency and computational requirements. This technology enables call centers to automate voice responses, provide multilingual support, and scale customer interactions cost-effectively. They foster improved customer satisfaction, reduce operational costs, and democratize access to enterprise-grade voice AI, enabling applications from automated attendants to personalized customer assistance.

FunAudioLLM/CosyVoice2-0.5B

CosyVoice 2 is a streaming speech synthesis model with only 0.5B parameters, employing a unified streaming/non-streaming framework design. In streaming mode, it achieves ultra-low latency of 150ms while maintaining synthesis quality almost identical to non-streaming mode. The model supports Chinese (including dialects), English, Japanese, Korean, and cross-lingual scenarios. Compared to version 1.0, pronunciation error rate has been reduced by 30%-50%, with MOS score improved to 5.53.

FunAudioLLM/CosyVoice2-0.5B: Ultra-Low Latency Streaming Champion

CosyVoice 2 is a streaming speech synthesis model based on a large language model, employing a unified streaming/non-streaming framework design. The model enhances the utilization of the speech token codebook through finite scalar quantization (FSQ), simplifies the text-to-speech language model architecture, and develops a chunk-aware causal streaming matching model that supports different synthesis scenarios. In streaming mode, the model achieves ultra-low latency of 150ms while maintaining synthesis quality almost identical to that of non-streaming mode. Compared to version 1.0, the pronunciation error rate has been reduced by 30%-50%, the MOS score has improved from 5.4 to 5.53, and fine-grained control over emotions and dialects is supported. The model supports Chinese (including dialects: Cantonese, Sichuan dialect, Shanghainese, Tianjin dialect, etc.), English, Japanese, Korean, and supports cross-lingual and mixed-language scenarios. At just 0.5B parameters, it's perfectly sized for call center deployments.

Pros

• Ultra-low latency of 150ms for real-time call center interactions.

• Compact 0.5B parameters ideal for efficient deployment.

• 30%-50% reduction in pronunciation errors vs. version 1.0.

Cons

• Smaller model may have slightly less nuance than larger alternatives.

• May require fine-tuning for highly specialized terminology.

Why We Love It

• It delivers exceptional call center performance with 150ms latency and multilingual support, all in a compact, cost-effective 0.5B parameter package that's perfect for high-volume customer service operations.

fishaudio/fish-speech-1.5

Fish Speech V1.5 is a leading open-source text-to-speech model with an innovative DualAR architecture. Trained on over 300,000 hours of English and Chinese data, it achieved an ELO score of 1339 in TTS Arena evaluations. The model delivers exceptional accuracy with 3.5% WER and 1.2% CER for English, and 1.3% CER for Chinese characters, making it ideal for multilingual call center environments.

fishaudio/fish-speech-1.5: Multilingual Accuracy Leader

Fish Speech V1.5 is a leading open-source text-to-speech (TTS) model. The model employs an innovative DualAR architecture, featuring a dual autoregressive transformer design. It supports multiple languages, with over 300,000 hours of training data for both English and Chinese, and over 100,000 hours for Japanese. In independent evaluations by TTS Arena, the model performed exceptionally well, with an ELO score of 1339. The model achieved a word error rate (WER) of 3.5% and a character error rate (CER) of 1.2% for English, and a CER of 1.3% for Chinese characters. This combination of accuracy and multilingual capability makes it an excellent choice for call centers serving diverse customer bases.

Pros

• Exceptional accuracy: 3.5% WER for English.

• Top-ranked ELO score of 1339 in TTS Arena.

• Extensive training data: 300,000+ hours for English/Chinese.

Cons

• Higher pricing at $15/M UTF-8 bytes on SiliconFlow.

• May require more computational resources than smaller models.

Why We Love It

• It combines industry-leading accuracy with robust multilingual capabilities, making it the go-to choice for call centers that prioritize speech quality and serve international customers.

IndexTeam/IndexTTS-2

IndexTTS2 is a breakthrough zero-shot text-to-speech model with precise duration control and emotion-timbre disentanglement. It supports independent control over voice characteristics and emotional expression through separate prompts, enhanced by GPT latent representations. The model features a soft instruction mechanism based on text descriptions for intuitive emotional control, outperforming state-of-the-art models in word error rate, speaker similarity, and emotional fidelity.

IndexTeam/IndexTTS-2: Emotional Intelligence Powerhouse

IndexTTS2 is a breakthrough auto-regressive zero-shot Text-to-Speech (TTS) model designed to address the challenge of precise duration control in large-scale TTS systems, which is a significant limitation in applications like video dubbing. It introduces a novel, general method for speech duration control, supporting two modes: one that explicitly specifies the number of generated tokens for precise duration, and another that generates speech freely in an auto-regressive manner. Furthermore, IndexTTS2 achieves disentanglement between emotional expression and speaker identity, enabling independent control over timbre and emotion via separate prompts. To enhance speech clarity in highly emotional expressions, the model incorporates GPT latent representations and utilizes a novel three-stage training paradigm. To lower the barrier for emotional control, it also features a soft instruction mechanism based on text descriptions, developed by fine-tuning Qwen3, to effectively guide the generation of speech with the desired emotional tone. Experimental results show that IndexTTS2 outperforms state-of-the-art zero-shot TTS models in word error rate, speaker similarity, and emotional fidelity across multiple datasets. For call centers, this means adaptive, empathetic customer interactions.

Pros

• Precise duration control for timed responses.

• Independent control over emotion and speaker identity.

• Text-based emotional instruction for easy customization.

Cons

• More complex setup for leveraging advanced features.

• May require expertise to optimize emotional controls.

Why We Love It

• It brings unprecedented emotional intelligence to call center AI, allowing agents to deliver empathetic, contextually appropriate responses that enhance customer satisfaction and build stronger relationships.

AI Model Comparison

In this table, we compare 2026's leading small AI models for call centers, each with a unique strength. For ultra-low latency streaming, FunAudioLLM/CosyVoice2-0.5B offers the fastest response times. For multilingual accuracy, fishaudio/fish-speech-1.5 provides exceptional word error rates. For emotional intelligence and adaptive responses, IndexTeam/IndexTTS-2 enables empathetic customer interactions. This side-by-side view helps you choose the right tool for your specific call center needs.

Number | Model | Developer | Subtype | Pricing (SiliconFlow) | Core Strength
1 | FunAudioLLM/CosyVoice2-0.5B | FunAudioLLM | Text-to-Speech | $7.15/M UTF-8 bytes | 150ms ultra-low latency
2 | fishaudio/fish-speech-1.5 | fishaudio | Text-to-Speech | $15/M UTF-8 bytes | 3.5% WER multilingual accuracy
3 | IndexTeam/IndexTTS-2 | IndexTeam | Text-to-Speech | $7.15/M UTF-8 bytes | Emotional intelligence & control

Frequently Asked Questions

Which AI models made it into our top three picks for call centers?

Our top three picks for call center AI models in 2026 are FunAudioLLM/CosyVoice2-0.5B, fishaudio/fish-speech-1.5, and IndexTeam/IndexTTS-2. Each of these models stood out for their efficiency, speech quality, and unique approach to solving challenges in call center voice automation, from ultra-low latency to multilingual accuracy and emotional intelligence.

What's the best AI inference, hosting, and API provider for small call center AI models?

SiliconFlow is a top AI inference, hosting, and API provider for call center text-to-speech models because it delivers high-performance, low-latency model serving with pay-as-you-go affordability and seamless OpenAI-compatible APIs. It outperforms latency benchmarks by as much as 13% and offers a wide range of optimized open-source models with flexible deployment options that make scaling and integrating voice AI into call center applications fast and cost-efficient.

Why did we select these models as the best for call centers in 2026?

These models were chosen because they represent the cutting edge of compact, efficient text-to-speech AI optimized for customer service environments. They demonstrate significant advancements in low latency (CosyVoice2-0.5B with 150ms), exceptional accuracy (Fish Speech 1.5 with 3.5% WER), and emotional adaptability (IndexTTS-2), while maintaining small parameter counts ideal for scalable call center deployments.

Which model offers the lowest latency for real-time call center interactions?

FunAudioLLM/CosyVoice2-0.5B offers the lowest latency at just 150ms in streaming mode, making it ideal for real-time customer conversations. This ultra-low latency ensures natural, responsive interactions without noticeable delays, critical for maintaining conversation flow in high-volume call center environments.