Why voice command is not working?

Voice assistants and voice command technology have become increasingly popular in recent years. Digital assistants like Siri, Alexa, and Google Assistant allow users to interact with devices through voice instead of touch. These assistants use natural language processing and speech recognition to understand commands and respond to queries. Voice control provides a hands-free, convenient way to get information, automate tasks, and access services on smartphones, smart speakers, vehicles, and other connected devices.

Lack of Accuracy

Poor voice recognition accuracy results in commands being misunderstood or misinterpreted. Even if the user speaks clearly, issues with voice recognition technologies prevent them from accurately processing and understanding natural speech. According to Dengel (https://www.linkedin.com/pulse/voice-recognition-accuracy-responsiveness-shaping-future-dengel), unless a system has been trained on your specific voice, you can expect accuracy no higher than 80-85%. This lack of accuracy significantly reduces the usefulness of voice commands.

For example, when trying to dictate a text message, voice recognition errors could completely change the meaning. Or when asking a voice assistant like Siri or Alexa a question, the wrong words may be detected, leading to an irrelevant or unhelpful response. Accuracy issues are especially pronounced with certain groups, like those with strong accents or speech impediments. Overall, poor accuracy makes consumers lose trust in voice interfaces.

Background Noise

Background noise can significantly impact the accuracy of voice commands How to Design Voice Assistants for Noisy Environments. Voice assistants rely on speech recognition technology, which analyzes the audio input to determine the words being spoken. However, background noises like music, talking, traffic, etc. can distort the audio input and make it more difficult for the speech recognition system to isolate the speech from the noise.

Studies have shown that as background noise increases, the error rate in speech recognition systems also increases. Even at a moderate noise level of 70dB (similar to the noise level of a vacuum cleaner), word error rates double compared to clear audio conditions Speech Recognition in Natural Background Noise. This is because the algorithms have a harder time separating the speech from the ambient sounds.

To improve accuracy in noisy environments, voice assistants need to utilize noise cancellation and audio filtering techniques. They also need to be trained on diverse audio samples that include real-world background noises, so they can learn to distinguish speech from noise more robustly.

Unnatural Speech

One of the biggest issues with voice commands is the need to speak in an unnatural, clear, and slow manner for the technology to understand you properly. As noted in research from Kambeyanda, discrete speech dictation systems require the user to insert brief but distinct pauses after each spoken word. This is very different from normal conversational speech patterns and cadence. Users must consciously adapt their speech to be more robotic and pronounced. According to Summa Linguae, the audio data used to train voice recognition systems does not include natural conversations and idioms. As a result, the technology struggles with colloquial speech and expressions.

Having to speak clearly and slowly in simple terms is frustrating and ruins the user experience. It feels unnatural and inhibits natural conversation flow. The technology still has a long way to go before it can fully understand casual, conversational speech at a normal pace and cadence.

Limited Vocabulary

One key limitation of voice assistants currently is their restricted vocabulary. Voice assistants like Siri, Alexa, and Google Assistant only recognize a fraction of the words in the English language, ranging from tens of thousands of words up to around 100,000 based on some estimates.

For comparison, the average native English speaking adult has a vocabulary of around 20,000-35,000 words. Even very educated adults generally have vocabularies only in the range of 40,000-50,000 words. Meanwhile, a tool like Google Search is able to understand millions of words and phrases.

This limited vocabulary means voice assistants frequently struggle with recognizing uncommon words and names. They also lack understanding of most specialized terminology unless it has been specifically programmed in. Without a broader vocabulary, voice assistants face challenges accurately interpreting natural conversational speech.

According to an article published in Nature (https://www.nature.com/articles/s41746-019-0133-x), a study found Alexa, Siri and Google Assistant could only understand about 30% of medication name questions asked by participants, largely due to the drug terminology being outside of their vocabulary.

Requires Internet

Most voice assistants like Siri, Alexa, and Google Assistant need an active internet connection to understand and process voice commands. This is because the speech recognition and natural language processing happens in the cloud, on servers operated by Apple, Amazon, Google etc. When you give a voice command to your phone or smart speaker, the audio is streamed to the company’s servers to analyze and interpret what you said, formulate a response, and send it back to your device. Without an internet connection, this communication is not possible.

As per the SmartThings community, their voice control platform requires internet connectivity to get voice commands to SmartThings services in the cloud. Google Assistant also needs internet to execute most commands, though it has some basic offline capabilities.

Enabling offline voice recognition requires on-device processing power, which is limited on smartphones and speakers. Companies are working on improving offline capabilities, but for now, an internet connection remains necessary for a fully functional voice assistant experience.

Security Concerns

There are growing security concerns over voice command technology and the risks of hacking or unauthorized access, especially with smart home devices.

Many voice assistants like Amazon Alexa and Google Home are always online and connected to the internet via WiFi. This leaves them vulnerable to cyber attacks from hackers that could gain access to the microphone and camera (Source). Hackers could potentially listen in on private conversations in your home or view camera footage without authorization.

There have been examples of hackers gaining access to smart speakers and being able to have full conversations while the owner was unaware (Source). This raises concerns over privacy and control of these always-on devices with microphones in our personal spaces.

Users should be aware of the risks associated with voice-activated technology and take steps to secure devices, monitor network activity, and be cautious of the sensitive information that is stored and transmitted through these systems. Manufacturers also need to prioritize security in the development of voice command devices and AI assistants.

Privacy Concerns

One major issue with voice assistants is the privacy concerns over continuous recording and data collection. Voice assistants like Amazon Alexa and Google Assistant are always listening for their wake words in order to respond to voice commands. This means they are passively recording conversations in your home which raises concerns over how this data is stored and used (FTC).

While companies claim recordings are only kept until they are processed, there have been instances of employees listening to private conversations for quality control purposes. There is also potential for hackers to gain access to these recordings (Kardome).

Users should be aware of these privacy risks, review privacy policies, and take steps to delete recordings if they are uncomfortable with how data is handled. Voice command may not feel as private as expected.

Lack of Context

One of the biggest challenges facing voice assistants like Google Assistant or Amazon Alexa is their lack of environmental context. When a human talks to another human, they naturally provide context through their tone of voice, body language, and ability to refer to things in their shared environment. Voice assistants don’t have access to any of this contextual information. As noted in an article on UX design, “We are not creating conversations, we are building old-school commands hidden behind voice requests. … They lack context in speech and not truly understand human conversations” (Source).

For example, if you say “turn it off” to a voice assistant, it has no way of knowing what “it” refers to without additional clarification. Humans implicitly understand context and intent based on factors like what was just being discussed or what objects are nearby. Voice assistants like Google Assistant rely solely on speech input and lack this critical environmental context. As a result, they struggle to interpret requests accurately, especially ones involving pronouns or incomplete thoughts. Users end up having to precisely specify what they want in an unnatural way for the technology to understand. This makes voice control tedious compared to natural human conversation where intent and context are quickly inferred.

Conclusion

In summary, voice command technology still faces several key limitations and challenges that prevent it from working perfectly. These include lack of accuracy, difficulty with background noise, the need for unnatural speech, limited vocabulary, reliance on internet connectivity, and concerns around security and privacy. While voice assistants like Siri, Alexa and Google Assistant have made major advances, they still struggle to understand natural speech and contextual commands. Users frequently need to repeat themselves, speak unusually clearly, or reformulate requests for voice command to work properly. Until voice recognition AI can better comprehend diverse voices and spontaneous speech, it will remain an imperfect technology. However, with continued research and innovation, voice interfaces may someday operate as seamlessly as human conversations.

Overall, the main barriers today are inaccurate speech transcription, inability to handle ambient sound, restricted capabilities, dependence on cloud processing, and risks to personal data. As developers aim to improve acoustic modeling, contextual awareness, and privacy protections, voice command may eventually become an intuitive hands-free interface. But for now, its limitations prevent seamless usage for many real-world applications.