Artificial Intelligence (AI) has made significant strides in recent years, with voice assistants becoming increasingly prevalent in various devices and applications. However, when it comes to integrating AI voices into landline phones, several challenges will stop it from becoming widespread; for now.
1. Audio Quality Limitations
Landline phones typically operate at a standard sample rate of 8kHz, which just means it’s of a low quality compared to what modern microphones can pick up. This reduced audio fidelity poses challenges for AI voice recognition systems, which perform optimally with higher-quality audio inputs. This is a limitation that can be overcome once there is enough data trained on lower quality audio, but for now, this isn’t readily available. Additionally, once landline phones transition away from
2. Conversational Context and Length
AI voice assistants are designed to handle brief interactions, such as setting reminders or providing weather updates. However, phone conversations often require maintaining context over extended periods, which is challenging for current AI systems. In addition, receiving a call at your business location is already loaded with a whole bunch of context, that many AI systems won’t have by default. For example, if you’re a Pizza store, your staff already has the context that a customer is calling your Pizza store, likely to grab a delicious slice.
3. Audio Quality Challenges
Voice assistants can present unique challenges in terms of audio quality. Issues such as background noise or having multiple voices speaking concurrently can affect its ability to understand the caller. For example, current AI models wait until silence until it starts processing a response – humans don’t do this. Humans stream data and combined contextual information subconsciously to provide a response in sub-second speed (most of the time at least).
4. Diversity in Speech Patterns
Human speech is incredibly diverse, encompassing various accents, dialects, and colloquialisms (eg: G’day maate). AI systems often struggle to accurately recognize and interpret this diversity, especially when trained on limited datasets. This limitation can lead to misunderstandings and errors in communication, reducing the effectiveness of AI voice assistants in landline applications.
What is AI Good at Right now?
AI makes complex tasks simpler. For example, it streamlines software development by translating human language into code.
At Voicee, we saw how this AI capability could enhance our Call Flow Editor, helping businesses revolutionize their call experience.
“When a call comes in between 12 PM and 5 PM, Monday to Friday, send it to voicemail.”
– and just like that, AI can build a Call flow using Voicee’s call flow editor for you.
In conclusion, while AI voice technology has advanced considerably, its application in landline phone systems remains constrained by technical limitations and infrastructure challenges. Overcoming these hurdles will require continued research and development, but for now, it’s not really viable for phone systems.