紧急时通过生成语音突发向通话中用户传递关键信息
Generative Voice Bursts during Phone Call
- 用生成式AI根据上下文自动生成简短语音消息
- 高优先级消息可突破传统呼叫等待限制,发送N次,间隔G秒
- 适合急救、灾害响应等需要快速传递信息的场景
在紧急情况下,传统移动电话无法将求救语音信息传递给正在通话中的接收者。标准呼叫等待提示既无法体现紧急程度,也无法传达等待来电的内容。本文提出一种新方法,在通话过程中向接收方传输生成式语音突发(Generative Voice Bursts)——即短时、上下文感知的音频消息,来自预授权或动态优先级提升的呼叫方。系统利用生成式AI技术,从位置、健康数据、图像、环境噪音等上下文输入自动合成语音消息,适用于呼叫方因失能或环境限制无法发声的情况。该方案结合语音、文本与优先级推理机制,使高优先级紧急信息可绕过常规呼叫等待屏障。采用GPT Neo生成文本,经语音合成后以配置间隔G秒、重复发送N次的方式送达,确保最小干扰的同时保留紧迫感。本方法对电信、手机制造及应急通信平台具有重要应用潜力。
原文摘要 · Abstract (English)
In critical situations, conventional mobile telephony fails to convey emergency voice messages to a callee already engaged in another call. The standard call waiting alert does not provide the urgency or content of the waiting call. This paper proposes a novel method for transmitting Generative Voice Bursts short, context aware audio messages during ongoing calls, from either preauthorized or dynamically prioritized callers. By leveraging generative AI techniques, the system automatically generates spoken messages from contextual inputs example like location, health data, images, background noise when the caller is unable to speak due to incapacitation or environmental constraints. The solution incorporates voice, text, and priority inference mechanisms, allowing high priority emergency messages to bypass conventional call waiting barriers. The approach employs models such as GPT Neo for generative text, which is synthesized into audio and delivered in configurable intervals G seconds and counts N times, ensuring minimal disruption while preserving urgency. This method holds potential for significant impact across telecom, mobile device manufacturing, and emergency communication platforms.
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