100 Best MATLAB Speech & Voice Videos

Notes:

MATLAB is a high-level programming language and environment for numerical computation, visualization, and programming. It is widely used in a variety of fields, including engineering, science, finance, and machine learning.

MATLAB can be used with speech and voice in a number of ways. For example, it can be used to process and analyze audio signals to extract speech features, such as pitch, spectral content, and speech rate. This can be useful for tasks like speech recognition, speaker identification, or language modeling.

MATLAB also includes a range of tools and functions for working with audio signals, such as functions for filtering, resampling, and visualization. These tools can be used to process and manipulate audio data, including speech and voice signals, in order to prepare them for further analysis or processing.

Additionally, MATLAB can be used to interface with other speech and voice technologies, such as speech synthesis or speech recognition engines. This can allow users to integrate these technologies into their own MATLAB-based applications and systems.

MATLAB can be used with dialog systems in a number of ways. Dialog systems are systems that are able to engage in natural language conversations with users, and can be used in a variety of applications, such as virtual assistants or chatbots.

One potential use of MATLAB with dialog systems is in the development and testing of dialog algorithms and models. MATLAB’s high-level programming language and powerful numerical computation capabilities can be used to implement and evaluate different dialog algorithms, such as those for natural language understanding, dialogue management, or response generation. This can help developers to quickly prototype and experiment with different dialog strategies, and to evaluate their performance.

MATLAB can also be used to process and analyze audio data in dialog systems. For example, it can be used to extract speech features from audio signals, such as pitch, spectral content, or speech rate. This can be useful for tasks like speech recognition, speaker identification, or language modeling, which are important components of many dialog systems.

Additionally, MATLAB can be used to interface with other speech and voice technologies that are used in dialog systems. For example, it can be used to control a speech synthesis engine to generate speech output, or to interface with a speech recognition engine to transcribe user input. This can allow users to integrate these technologies into their own MATLAB-based dialog systems.

Speech classification is the process of automatically assigning a speech signal to a pre-defined class or category based on its characteristics. This can be useful for tasks like speech recognition, where a speech classifier can be used to identify the words or phrases that are present in the speech signal. Speech classification algorithms can use a variety of techniques, such as machine learning or signal processing, to analyze the speech signal and make a classification decision.
Speech coder, also known as a speech codec, is a type of algorithm or system that is used to compress or encode speech signals for efficient transmission or storage. Speech codecs use a variety of techniques, such as compression and quantization, to reduce the amount of data needed to represent a speech signal. This can be useful for applications like telephony or voice over internet protocol (VoIP), where it is important to transmit speech signals with minimal bandwidth or storage requirements.
Speech conversion, also known as speech transformation or speech modification, refers to the process of changing the characteristics of a speech signal in some way. This can include things like changing the pitch or speaking rate of the speech, or converting the speech from one language to another. Speech conversion algorithms can use a variety of techniques, such as signal processing or machine learning, to modify the speech signal in a desired way.
Speech converter is a specific type of system or tool that is designed to perform speech conversion. This can include things like software programs or online tools that allow users to input a speech signal and convert it in some way, such as by changing the pitch or speaking rate.
Speech emotion refers to the emotional content or state that is expressed in a speech signal. This can include things like happiness, sadness, anger, or fear, as well as more subtle emotional cues such as emphasis or hesitation. Speech emotion can be important in applications like speech recognition or natural language processing, where the emotional state of the speaker can affect the meaning or interpretation of the speech.
Speech emotion recognition is the process of automatically recognizing the emotional content or state that is expressed in a speech signal. This can involve analyzing the speech signal to extract features that are indicative of different emotions, such as pitch, speaking rate, or spectral content, and using these features to make a classification decision. Speech emotion recognition algorithms can use a variety of techniques, such as machine learning or signal processing, to analyze the speech signal and make an emotion recognition decision.
Speech enhancement refers to the process of improving the quality or intelligibility of a speech signal. This can involve techniques like noise reduction, dereverberation, or equalization, which are used to remove or reduce unwanted noise or distortion in the speech signal. Speech enhancement algorithms can use a variety of techniques, such as signal processing or machine learning, to improve the quality of the speech signal.
Speech generator is a type of system or tool that is designed to automatically generate speech signals. This can involve using algorithms or other methods to synthesize speech based on input text or other data. Speech generators can be useful for applications like text-to-speech systems, where they are used to convert written text into audible speech.
Speech oscilloscope is a type of tool or instrument that is used to visualize and analyze speech signals. A speech oscilloscope typically displays a graphical representation of the speech signal over time, allowing users to see the variation in the signal’s amplitude or other characteristics. This can be useful for tasks like speech analysis or speech synthesis, where it is important to understand the characteristics of the speech signal.
Speech processing refers to the field of study and technology that deals with the analysis, manipulation, and generation of speech signals. This can include things like speech recognition, speech synthesis, and speech emotion recognition, as well as more general techniques for working with speech signals, such as signal processing or machine learning. Speech processing technologies are used in a variety of applications, such as speech recognition systems, speech synthesis systems, and speech therapy tools.
Speech recognition is the process of automatically recognizing the words or phrases that are present in a speech signal. This can involve analyzing the speech signal to extract features that are indicative of different words or phrases, and using these features to make a recognition decision. Speech recognition algorithms can use a variety of techniques, such as machine learning or signal processing, to analyze the speech signal and make a recognition decision.
Speech recording refers to the process of capturing a speech signal, typically by using a microphone or other type of audio recording device. Speech recordings can be stored in a digital format, such as a WAV or MP3 file, for later analysis or processing. Speech recordings are commonly used in applications like speech recognition or speech synthesis, where the recorded speech is used as input to a speech processing system.
Speech separation, also known as source separation or speech extraction, refers to the process of separating a mixture of speech signals into its individual components. This can be useful in applications like speech recognition, where the goal is to recognize the words or phrases that are present in the speech signal. Speech separation algorithms can use a variety of techniques, such as signal processing or machine learning, to separate the individual speech sources from the mixture.
Speech signal is an electrical or digital representation of the sounds produced by a speaker’s vocal cords. Speech signals can be represented in a variety of ways, such as a waveform or spectrogram, and can be processed and analyzed using a variety of techniques, such as signal processing or machine learning. Speech signals are commonly used in applications like speech recognition, speech synthesis, and speech therapy.
Speech synthesis is the process of generating speech signals from written or other input data. This can involve using algorithms or other methods to synthesize speech that sounds similar to human speech, based on input text or other data. Speech synthesis algorithms can use a variety of techniques, such as concatenative synthesis or formant synthesis, to generate speech signals that are natural and intelligible. Speech synthesis is commonly used in applications like text-to-speech systems, where written text is converted into audible speech.
Speech to text, also known as automatic speech recognition or ASR, is the process of automatically transcribing speech signals into written text. This can involve analyzing the speech signal to extract the words or phrases that are present in the speech, and converting them into written text. Speech to text algorithms can use a variety of techniques, such as machine learning or signal processing, to analyze the speech signal and generate the corresponding written text.
Speech vocoder is a type of algorithm or system that is used to encode and decode speech signals for efficient transmission or storage. Speech vocoders use a variety of techniques, such as linear predictive coding or code-excited linear prediction, to represent the speech signal in a compact and efficient form. This can be useful for applications like telephony or voice over internet protocol (VoIP), where it is important to transmit speech signals with minimal bandwidth or storage requirements.

Wikipedia: