Internet
How Do Collect and Train Data for Speech Projects?
Data collection is the process of gathering, analyzing, and, measuring accurate data from diverse systems to use for business process decision-making, speech projects, and research.
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With technology evolution, we are moving towards machine learning systems that can understand what we say. In our daily lives, we all have encountered many virtual assistants like Alexa, Siri, and others. These virtual assistants often help us in tuning the lights in our homes, finding information on the internet, and even starting a video conference. But do you know how it does that?
To produce results, these virtual assistants use natural language processing to understand the user’s intent. Natural Language Processing technology enables virtual assistants to understand user intent and produce outcomes. These virtual assistants are applications of automatic speech recognition and are also known as speech recognition software. This software uses machine learning and NLP to analyze and convert human speech data into text.
But, attaining maximum efficiency of this software requires the collection of substantial speech and audio datasets. The purpose of collecting these audio datasets is to have enough sample recordings that can be fed into automatic speech recognition (ASR) software.
Furthermore, these datasets can be used against the speakers using unspecified speech recognition models. And to make ASR software work as intended, speech data collection and audio datasets must be conducted for all target demographics, locations, languages, dialects, and accents.
Artificial Intelligence can be as intelligent as the data given to it. Hence, collecting data for feeding the machine learning model is a must to maximize the effect of ASR. Let’s discuss steps in speech data collection for effective automatic speech recognition training.
Table of Contents
1. Create a Demographic Matrix
For creating a demographic matrix, the enterprise must consider the following information like language, locations, ages, genders, and accents. Along with these, it is a must to note down a variety of information related to environments like busy streets, waiting rooms, offices, and homes. Enterprises can also consider the devices people are using like mobile phones, headsets, and a desktop.
2. Collect and transcribe speech data
To train the speech recognition model, gather speech samples from real humans and take the help of a human transcriptionist to take notes of long and short utterances by following your key demographic matrix. In this way, human is a vital part of building proper audio datasets and labeled speech and further development of applications.
3. Build a separate test data
Once the text subscription is completed, it’s time to pair the transcribed test with the corresponding audio data and segment them to include one statement in each. Later on, take the segmented pairs and extract a random 20% of the data to form a set for testing.
4. Train the language model
To maximize the effectiveness of the speech recognition model, you can train the language model by adding general additional text that was not additionally recorded. For example in canceling a subscription, you recorded one statement that ‘I want to cancel my subscription, but you can also add texts like “Can I cancel my subscription” or “I want to unsubscribe”. To make it more effective and catchy you can also add expressions and relevant jargon.
5. Measure and Iterate
The last and most important step is to evaluate the output of automatic speech recognition software to benchmark its performance. In the next step take the trained model and measure how well it predicts the test set. In case of any gaps and errors, engage your machine learning model in the loop to yield the desired output.
Conclusion
From travel, transportation, media, and entertainment, the use of speech recognition software is evident. We all have been using voice assistants like Alexa and Siri to complete some of our routine tasks. To effectively use this speech recognition software requires proper training in the audio datasets and the use of relevant data for the machine learning model.
Proper execution and the right use of data make sure the speech recognition software going to work efficiently and enterprises can scale them for further upgrades and development. As data and speech recognition go hand in hand, make sure you are using data with the right approach.
Games
Parimatch starts cooperation with the AFA in Asia
This partnership allows the AFA to expand its international presence and, together with Parimatch, participate in all sports technology events held in Asia.
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The global gaming platform Parimatch has announced a new exclusive partnership with the Argentine Football Association (AFA), becoming the organization’s fifth regional sponsor. This partnership allows the AFA to expand its international presence and, together with Parimatch, participate in all sports technology events held in Asia.
Expanding its horizons, the Argentine Football Association is actively entering new strategic markets, involving more than 55 commercial partners. In addition, the association is improving its digital content strategy, including social media in five languages, to help attract new audiences.
The partnership with Parimatch will provide users with the opportunity to participate in various official events, receive autographed t-shirts of the players of the national team of Argentina, and enjoy unique moments thanks to this collaboration.
AFA President Claudio Tapia said: “We express our gratitude to Parimatch, a leading company in the gaming industry, for joining the Argentine football family as a regional sponsor of our national team in the Asian region.”
Tapia stressed that the AFA continues to take active steps to expand its presence in strategic markets and forge alliances with leading companies. This agreement allows the association to work actively in Asia and strengthens its position in the world of football. “We sincerely welcome Parimatch as our regional sponsor,” he added.
The AFA’s Commercial and Marketing Director, Leandro Petersen, stated: “We are delighted to announce a new regional sponsorship in the Asian region between the AFA and Parimatch. This partnership with a market leader like Parimatch will strengthen our position in the international arena and help expand the fan base of the Argentine national team in Asia.”
The press service of Parimatch also expressed satisfaction with the cooperation, underscoring: “We are pleased to work with the Argentine Football Association as its regional sponsor in Asia. This agreement marks an important milestone for Parimatch as we enhance our commitment to growing football in Asia and providing an exceptional playing experience for fans. Our partnership with the AFA allows us to expand our brands and actively engage with football fans in Asia.”
Parimatch reaffirms its commitment to supporting football in Asia and is ready to provide fans with unforgettable experiences as a regional sponsor of the Argentine Football Association.
Through strategic partnerships with leading football organizations such as the AFA, Parimatch continues to promote the development of sports and popularize football culture in Asia, bringing beloved teams closer to their fans.
Parimatch also plays a key role in promoting sports culture in the region. Through its partnership with the AFA, Parimatch provides its users with exclusive access to events and products related to Argentine football. This not only strengthens the Parimatch brand, but also enhances the commitment to sports in Asia.
The collaboration between Parimatch and the AFA demonstrates how strategic alliances can influence the development of the sports industry. Parimatch is constantly looking for new opportunities for development and innovation, and this partnership is another step in that direction. Parimatch users are looking forward to new opportunities that will open up thanks to this collaboration.
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