# A Systematic Review of Accessibility Techniques for Online Platforms: Current Trends and Challenges
## 3 Results of the Systematic Review
### Relevant Solutions Based on Speech Recognition  
Voice recognition technology powers secure user authentication and personalized experiences. Applications include voice-based biometrics in banking (e.g., Wells Fargo's voice authentication [6]), smart home devices (e.g., Google Nest), and call centers for customer identity verification. Challenges in voice recognition include handling variations in voice due to health, age, and emotional state, which can lead to inaccuracies and frustrations in sensitive contexts like financial services. Advancements in ASR technologies have shown varied accuracy rates among leading solutions, with notable performances from providers like Whisper and Speechmatics [7]. These findings highlight the importance of evaluating ASR systems not only for their accuracy but also for their accessibility features. Research indicates that voice-controlled personal assistants, such as the Amazon Echo, are beneficial for users with disabilities, particularly for those with speech impairments [8]. The positive user feedback underscores the potential of these technologies to enhance communication and interaction in daily life. [PERSON], [PERSON] et al. discuss in their work the growing role of voice control technology, particularly AI-based voice assistants used in smartphones and laptops [9]. These assistants recognize human voice, convert it to text, and then use the Google text-to-speech (GTTS)engine to produce audio in English, which is played back using Python's (both 2.7 and 3.x versions) play sound package. Also, the study of [PERSON], [PERSON] et al. explores the accessibility of voice-controlled personal assistants like the Amazon Echo for users with disabilities. Analysis of 346 reviews and interviews with 16 visually impaired users show that, despite some challenges, many, including those with speech impairments, find the device helpful, with 59.4% of reviews on SR being positive and 74.2% of speech-impaired users reporting satisfaction [8]. Another interesting study conducted by [PERSON], [PERSON] et al. says that voice-activated personal assistants (VAPAs), like Siri and Alexa, benefit users, especially those with visual impairments [10]. This study reviews design guidelines from major companies, highlighting the assumption that VAPAs should mimic human conversation. It critiques this approach and suggests improvements to enhance usability for all users. On the other hand, [PERSON], [PERSON] et al. demonstrates that the Two Microphone Authentication system can accurately localize audio sources within a narrow cone of less than 30 deg while achieving zero false positives [11]. It effectively eliminates replay attacks and prevents the injection of inaudible or hidden commands, significantly enhancing the security of voice-controlled interfaces. [PERSON], [PERSON] et al. review and compare various cloud-based natural language understanding platforms developed over the last decade. It presents a taxonomy for six platforms and conducts a performance evaluation of three of them, highlighting their respective strengths and weaknesses. The analysis reflects the widespread adoption of these tools in chat services and conversational assistants on mobile devices [12]. [PERSON], [PERSON] et al. present an SR system designed to help arm-disabled students to control computers by voice, enhancing accessibility in education. The system uses two approaches: one based on voice activity detection and Mel-frequency cepstral coefficients and another using discrete wavelet transform with modified MFCC. The first approach achieved a recognition rate of 98.7%, while the second achieved a rate of 98.86%, offering higher accuracy but slower processing [13]. In order to explore recent advancements in accessibility research, [PERSON], [PERSON] et al. situates voice-based accessibility within existing theoretical frameworks, discusses design challenges, and identifies opportunities for interdisciplinary collaboration in this area [14]. In the same context, [PERSON], [PERSON] et al.