Advanced Mac OS Speaker Detection App

Hi, How are you? Very happy to bid your project because my skills are fitted in your project. I am a AI engineer with 8 years of experience in machine learning, deep learning, data science, OCR, NLP and AI. I am very familiar with could computing, chatGPT, YOLO, GPU, Mediapipe, Generative Adersarial Network, openAI, Mask R-CNN, CNN, RNN, GAN, LSTM, SVM, reinforement learning, opencv, Pytorch, tensorflow, keras, tesarret Pandas, sklearn, numpy, matplotlib, seaborn and so on. I have made app for speaker recognition, speech recognition, sentiment classification, signal recognition. I can do your project perfectly. If you send the message , we can discuss the project more. Thanks.

I am a proficient Mac OS & Python application developer with extensive experience in speech recognition technology. I can quickly develop a high-accuracy speaker detection app for your large collection of mono Wav files. My in-depth understanding of audio analysis algorithms ensures the delivery of accurate reports, meeting your requirements. Let's discuss further details and fixed pricing for this project.

Hello Good afternoon , I just finished reading the job description . I see you are looking for someone experienced in developing products using Mac OS, Artificial Neural Network, Recurrent Neural Network, Automatic Speech Recognition and Python. This is something I can do, Please review my profile to confirm that I have great experience working with these tech stacks. While I have few questions: 1. These are all the requirements? If not, Please share more detailed requirements. 2. Do you currently have anything done for the job or it has to be done from scratch? 3. What is the timeline to get this done? Why Choose Me? 1. I have done more than 250 major projects only on freelancer.com. 2. I have not received a single bad feedback since last 5-6 years. 3. You will find 5 star feedback on last 100+ major projects which shows my clients are happy with my work. Timings: 9am - 9pm Eastern Time (I work as a full time freelancer) My Portfolio: https://www.freelancer.com/u/AwaisChaudhry Please start the chat to discuss it further. Regards, Awais

Dear Rob N., As an experienced Python developer, I would like to express my strong commitment and enthusiasm to complete the Mac OS application project you've described. With a solid background in developing Python applications, I am confident in my ability to build a remarkable solution that meets your specific requirements. Throughout my career, I have successfully developed numerous applications for the Mac OS platform, demonstrating my expertise and understanding of its unique complexities. Additionally, I have extensive experience working with large collections of audio files, including Mono 32-bit 48kHz Wav files, similar to those you mentioned. This familiarity allows me to quickly grasp the intricacies of your project and design an efficient solution that fulfills your objectives. By choosing me, Dr. Zied B., as your dedicated freelancer, you will receive a highly committed professional who will devote considerable time and effort to deliver the outstanding results you deserve. Rest assured that I will diligently work to ensure the application is developed to your satisfaction, providing you with a final product that not only meets, but exceeds your expectations. Thank you for considering my bid. I am eager to collaborate with you and transform your vision into reality. Feel free to reach out to discuss your project in further detail. Sincerely, Dr. Zied B.

Hey!! I've 8+ years of experience as an native iOS and Mac OS developer. I've all latest iOS devices iPhone, iPad, iWatch and MacBook Pro etc. Contact me to solve your bugs as soon as possible. Waiting for your message in chat box. Thank you!!

Hi,i can deliver you the wrk within 4 days, utilizing my expertise in Python and Mac OS application development. I have profound experience in developing AI-based applications, and your project aligns perfectly with my skill set. My strong understanding of speech recognition technology and audio analysis algorithms will grant me a unique advantage to tackle the complexities involved in distinguishing between one or multiple speakers with a high degree of accuracy. I understand that prompt delivery is of utmost importance to you, and I strongly believe that I can meet your expectations while maintaining the quality you desire. My ten years of experience in the field have fostered great efficiency in my work process which contributes to quick development without compromising on the final product's performance or quality. Lastly, my commitment to open communication and client satisfaction is unwavering. I will continually seek your input and provide updates throughout the project timeframe so as to ensure our mutual understanding and alignment of goals. Given my skillset, experience, strong work ethics, and dedication to delivering outstanding work, I am confident that collaborating with me on this project will result in a highly effective, precise, and timely Advanced Mac OS Speaker Detection App exceeding your expectations. I look forward to discussing the project details further.

Hello there, I can help u with this job plz contact and initiate the chat so that we can discuss in detail. I have great experience with Python, Mac OS, Recurrent Neural Network, Artificial Neural Network and Automatic Speech Recognition. Meanwhile here is my profile: https://www.freelancer.com/u/ayesha0124

As an AI and Machine Learning expert with over a decade manning crucial development roles in established companies, I'm confident that I possess the skills and experience necessary to deliver an error-free, state-of-the-art MacOS Python app tailored to your exact needs. My proven expertise in computer vision, machine learning, deep learning, and image processing will prove invaluable as we tackle the unique challenges your project presents. Speaking to your specific requirements, my fluency with TensorFlow, Keras, PyTorch, and OpenCV will ensure our maximization of machine learning algorithms to drive superior speaker detection accuracy. Moreover, my grasp of big data technologies like Hadoop, Spark, and Apache Kafka uniquely equips me to not just comprehend but strategically handle your substantial WAV file collection. Lastly, my portfolio is packed with previous ventures that substantiate my skill set's depth and versatility. I stand not just as an app developer but as a problem solver who uses insights from various AI fields to craft practical solutions. Choosing me isn't just about optimum functionality; it's also about receiving a final product based on thorough industry knowledge that has reached new heights through my twelve-year repertoire. Shunning necessity for flattery but brimming with confidence that together we can render Your valuable project successful.

Hello Rob N. This is Arvie from Philippines. Since I have worked on similar projects and I am super-familiar with Python, Mac OS, Recurrent Neural Network, Automatic Speech Recognition and Artificial Neural Network. I believe that I'm the perfect person who can finish the project completely. Please contact me for further discussion and let's get started! Thanks and regards, Arvie.

Hello! I'm well-equipped to develop a Mac OS Python app for speaker detection in Mono, 24-bit, 48 kHz Wav files. My expertise includes: Python Application Development Mac OS Proficiency Speech Recognition Technology Audio Analysis Algorithms Artificial Neural Networks (ANN) Recurrent Neural Networks (RNN) Utilizing these skills, I'll ensure over 95% accuracy in detecting single or multiple speakers within nested directories.

Objective: Develop a Mac OS application in Python for detecting the number of speakers in mono WAV audio files with a focus on achieving over 95% accuracy. Key Features: User-friendly Mac OS interface for selecting audio file folders. Recursive folder scanning for WAV files. Integration of a speech recognition system supporting speaker diarization. Logic for determining the number of speakers and creating a report. Report generation for each processed audio file. Accuracy optimization and testing. Deliverables: Mac OS Application Package Documentation Source Code User Guide Assumptions and Dependencies: Availability of audio files in the selected folder. Access to a suitable speech recognition API or library. Project Risks: Achieving over 95% accuracy may be challenging and may require optimization. Compatibility issues on different Mac OS versions. Acceptance Criteria: The application accurately detects the number of speakers in audio files. The report clearly states "speakers = 1" or "speakers = 2 or more" with over 90% accuracy for the majority of files.