Computer-implemented method, computer program and computer system for audio quality feedback during live transmission from a source device

Abstract

To provide a method for audio quality feedback during live transmission from a source device.SOLUTION: The method comprises: obtaining audio information of an audio signal as received by at least some of multiple audience devices; classifying one or more subsets of the multiple audience devices by one or more common factors per subset; analyzing the obtained audio information from the multiple audience devices in conjunction with the classifications of the one or more subsets of the multiple audience devices to determine one or more common factors that affect received audio quality at an identified subset of the multiple audience devices classified by the one or more common factors; and providing feedback of the one or more common factors to at least one of the multiple audience devices in the identified subset or to the source device.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to audio quality feedback, and more particularly to audio quality feedback during live transmission from a source device. [Background technology]

[0002] Teleconferencing allows people to meet in different locations using telecommunications. The term "teleconference" can encompass audio conferences, video conferences, or more complex web conferences or webinars, such as those that include shared screens and chat interfaces.

[0003] Teleconferencing is often used for meetings where people in different locations work together. To communicate effectively, people can share their screens to display information, see the person speaking and other participants, and use chat windows for non-voice communication. These artifacts greatly enhance the teleconference experience. Summary of the Invention [Problem to be solved by the invention]

[0004] The present invention aims to provide a computer-implemented method, system and computer program product for audio quality feedback during live transmission from a source device. [Means for solving the problem]

[0005] According to a first aspect of the present invention, there is provided a computer-implemented method for audio quality feedback during live transmission from a source device received at a plurality of audience devices, the method being executed on a server and comprising: acquiring audio information of audio signals received by at least some of the plurality of audience devices in a transmission session; classifying one or more subsets of the plurality of audience devices by one or more common factors per subset; analyzing the acquired audio information from the plurality of audience devices using the classification of the one or more subsets of the plurality of audience devices to determine one or more common factors that affect the received audio quality at the identified subset of the plurality of audience devices classified by the one or more common factors; and providing feedback of the one or more common factors to at least one of the audience devices in the identified subset, or to the source device, or a combination thereof.

[0006] The described method has the advantage of determining groups of audience devices that experience the same quality of received audio from a source device in a live transmission and that have common factors that may be causing the quality of the received audio, and feedback is provided dynamically during the live transmission, allowing users of the audience devices or source devices, or a combination thereof, to take corrective action.

[0007] A method of obtaining audio information for an audio signal received by at least some audience devices in a transmission session may include obtaining an audio quality level determined at one audience device by processing the received audio signal. Processing the received audio signal may include converting the audio signal using a speech-to-text conversion process and analyzing the obtained text to assess the audio quality level. Analyzing the obtained text to assess the audio quality level may include determining a ratio of converted words to gaps in sample periods of the audio signal.

[0008] A method of obtaining audio information of audio signals received by at least some of a plurality of audience devices in a transmission session may include obtaining audio signal parameter data from the plurality of audience devices and comparing audio signal parameters of the plurality of audience devices to determine a subset of the plurality of audience devices having similar received audio signals.

[0009] Categorizing one or more subsets of the plurality of audience devices by one or more common factors per subset may include obtaining factor details for each audience device and grouping a subset of the plurality of audience devices with the same one or more factors, such that different subsets of audience devices are affected by an issue having one or more factors.

[0010] The method may further include analyzing the obtained audio information from the multiple audience devices to determine whether the audio information is below a threshold quality for all audience devices, and providing feedback to the source device that the overall received audio quality is below a required quality. If all or a majority of the audience devices are experiencing poor quality of the received audio signal, this indicates that a problem lies in the transmission from the source device and appropriate feedback may be provided.

[0011] The method may further include detecting a source device of a transmitted audio signal in the transmission session and determining from which audience device to obtain audio information in the transmission session. The source device may change during a live transmission as different users join the teleconference and the method accommodates this by detecting the current source device.

[0012] Analyzing the obtained audio information from the plurality of audience devices using the classification of the one or more subsets of the plurality of audience devices includes determining a correlation between one or more common factors and audio quality levels of the identified subsets, which determines a positive factor or combination of factors to be determined, as well as a negative factor or combination of factors to provide constructive feedback of positive factors that may improve the audio received by a user at the audience device.

[0013] The audio quality level may be one of a configurable range of audio quality levels from a low quality level to a high quality level, and a user may configure their preferred audio quality level to accommodate their accessibility requirements.

[0014] Categorizing the plurality of audience devices by a common factor may include categorizing by one or more of the following groups: location, communication channel, transmission medium, and configuration or type of audience device.

[0015] According to another aspect of the present invention, there is provided a computer-implemented method for audio quality feedback during live transmission from a source device received at a plurality of audience devices, the method being executed on a server and including: acquiring audio information of an audio signal received by at least some of the plurality of audience devices in a transmission session; acquiring factors associated with at least some of the plurality of audience devices in the transmission session; analyzing the audio information and the common factors to determine a correlation between the quality of the received audio signal and one or more common factors for a subset of the plurality of audience devices; and providing feedback of the one or more common factors to at least one of the plurality of audience devices in the subset, or to the source device, or a combination thereof.

[0016] Analyzing the audio information and the common factors may include analyzing the audio information in the form of quality levels and comparing the quality levels within and between groups of multiple audience devices having one or more common factors to determine a subset of multiple audience devices having a shared quality level.

[0017] According to yet another aspect of the present invention, there is provided a system for audio quality feedback during a live transmission from a source device received at a plurality of audience devices, the system comprising: a server having a processor and a memory configured to provide computer program instructions to the processor to perform functions of the feedback system, the feedback system comprising: an audio information acquisition component for acquiring audio information of audio signals received by at least some of the plurality of audience devices in a transmission session; a classification component for classifying one or more subsets of the plurality of audience devices by one or more common factors per subset; an analysis component for analyzing the acquired audio information from the plurality of audience devices using the classification of the one or more subsets of the plurality of audience devices to determine one or more common factors affecting the received audio quality at the identified subset of the plurality of audience devices classified by the one or more common factors; and a feedback component for providing feedback of the one or more common factors to at least one of the plurality of audience devices in the identified subset, or to the source device, or a combination thereof.

[0018] The system may include a feedback system component provided at an audience device, which may include an audio quality level component for obtaining an audio quality level determined at an audience device by processing the received audio signals, which may include a processing component at an audience device for processing the received audio signals, which may include a speech-to-text component for converting the audio signals using a speech-to-text process and analyzing the resulting text to assess the audio quality level.

[0019] The audio information acquisition component at the server may acquire audio signal parameter data from the plurality of audience devices, and the system may include an audio comparison component that compares audio signal parameters of the plurality of audience devices to determine a subset of the plurality of audience devices that have received similar audio signals.

[0020] The classification component may obtain details of the factors of each audience device and may group a subset of the audience devices with one or more of the same factors.

[0021] The system may include an overall quality component that analyzes the acquired audio information from the multiple audience devices to determine whether the audio information is below a threshold quality for all audience devices, and the feedback component provides feedback to the source device that the received overall audio quality is below a required quality.

[0022] The feedback component can dynamically provide feedback of one or more common factors during the live transmission.

[0023] The system at the server may include a device detection component for detecting source devices of transmitted audio signals in the transmission session and for determining from which audience devices to obtain audio information in the transmission session.

[0024] The analysis component may include a correlation component for determining a correlation between one or more common factors and an audio quality level of the identified subset. The audio quality level may be one of a range of audio quality levels from a low quality level to a high quality level. A configuration component may be provided for receiving a configuration of the audio quality level.

[0025] According to yet another aspect of the present invention, there is provided a system for audio quality feedback during a live transmission from a source device received at a plurality of audience devices, the system comprising: a server having a processor and a memory configured to provide computer program instructions to the processor to perform functions of the feedback system, the feedback system comprising: an audio information acquisition component for acquiring audio information of an audio signal received by at least some of the plurality of audience devices in a transmission session; a factor acquisition component for acquiring factors associated with at least some of the plurality of audience devices in the transmission session; an analysis component for analyzing the audio information and the common factors to determine a correlation between the quality of the received audio signal and one or more common factors for a subset of the plurality of audience devices; and a feedback component for providing feedback of the one or more common factors to at least one of the plurality of audience devices in the subset, or to the source device, or a combination thereof.

[0026] According to yet another aspect of the present invention, there is provided a computer program or computer program product for audio quality feedback during live transmission from a source device received at a plurality of audience devices, the computer program or computer program product causing a computer to acquire audio information of audio signals received by at least some of the plurality of audience devices in a transmission session, classifying one or more subsets of the plurality of audience devices by one or more common factors per subset, analyzing the acquired audio information from the plurality of audience devices using the classification of the one or more subsets of the plurality of audience devices to determine one or more common factors affecting the received audio quality at the identified subset of the plurality of audience devices classified by the one or more common factors, and providing feedback of the one or more common factors to at least one of the plurality of audience devices in the identified subset, or to the source device, or a combination thereof. The computer program product comprises a computer-readable storage medium having program instructions embodied thereon, the program instructions being executable by a computer to cause a processor to perform the method.

[0027] The computer-readable recording medium may be a non-transitory computer-readable recording medium, and the computer-readable program code may be executable by a processing circuit.

[0028] The subject matter which is regarded as the invention is particularly pointed out and distinctly claimed in the concluding portion of the specification. The invention, both as to organization and method of operation, together with its objects, features, and advantages, may best be understood by reference to the following detailed description of the invention when read in conjunction with the accompanying drawings. [Brief explanation of the drawings]

[0029] [Figure 1] FIG. 1 is a schematic diagram illustrating an example of teleconferencing in which embodiments may be implemented. [Figure 2] FIG. 2 is a flow diagram of an exemplary implementation of the described method, according to a server-implemented embodiment. [Figure 3A] FIG. 3A is a flow diagram of an exemplary implementation of the described method, according to an embodiment illustrating the interaction between a server and a user device. [Figure 3B] FIG. 3B is a flow diagram of another exemplary implementation of the described method, according to an embodiment illustrating the interaction between the server and the user device. [Figure 4] FIG. 4 is a block diagram of an exemplary embodiment of a system according to an embodiment of the present invention. [Figure 5] FIG. 5 is a block diagram of a computer system or cloud server on which embodiments may be implemented. [Figure 6] FIG. 6 is a schematic diagram of a cloud computing environment in which embodiments may be implemented. [Figure 7] FIG. 7 is a diagram of abstraction model layers of a cloud computing environment in which embodiments of the present invention may be implemented. DETAILED DESCRIPTION OF THE INVENTION

[0030] It will be appreciated that for simplicity and clarity of illustration, elements shown in the figures have not necessarily been drawn to scale. For example, the dimensions of some elements may be exaggerated relative to other elements for clarity. Furthermore, where considered appropriate, reference numerals may be repeated among the figures to indicate corresponding or analogous features.

[0031] Generally, the most important aspect of a teleconference is the audio in the teleconference. Without clear audio, participants have a hard time understanding what the speaker is saying, regardless of what they see through the display. An unclear audio signal can be caused by a variety of issues, including poor transmission from the speaker's device to the audience's devices, poor reception at the audience's devices, or the speaker's position relative to the speaker's microphone.

[0032] In the event of poor transmission or reception, the audience may ask the speaker to move or speak more clearly, however, the audience may continue to experience the same problem and time may be wasted trying to identify and solve the problem.

[0033] In other cases where poor audio is due to the speaker's location, repeatedly interrupting the meeting to ask the speaker to move is annoying to the audience and disruptive to the meeting.

[0034] The described methods and systems provide audio quality feedback during a live transmission from a source device that is received at multiple audience devices. This may be used during a teleconference, such as a telephone conference, video conference, web conference, or live broadcast of audio received and listened to by a distributed audience. The source device and the audience may each use a computing or telecommunications device to receive the transmitted audio. The audio transmitted during a teleconference in accordance with the described methods and systems may be voice audio. However, at least some of the described embodiments may be used with other types of audio transmission, such as live music or other types of audio.

[0035] The described methods use an assessment of received audio quality at an audience device during a transmission session, which may be measured using various described methods. Multiple audience devices participating in the transmission session are classified by common factors, such as the location of the audience device, the method of communication of the audience device with the source device, the type of device the audience device uses, etc. The analysis of the received audio quality and classification by common factors is used to determine one or more common factors that affect the received audio quality. A common factor may be any factor that may affect the quality of received audio shared by a group of participant devices. Feedback may be provided to the source device or the audience device, or a combination thereof, providing information regarding the determined common factors that may affect audio quality.

[0036] Feedback may be provided that a particular cellular network is problematic if poor audio quality is measured when received on a subset of audience devices that are classified as having the common factor of being connected via a mobile network operator's telephone network. Analysis of the common factor classification may, for example, identify that poor quality is being received with a combination of common factors using a particular mobile network operator's data network in a particular city.

[0037] If all audience devices receive the same poor quality audio, the problem can be identified as being source related, such as the position of the speaker relative to the microphone or background noise interference.

[0038] The method can also be used to determine common factors that result in very high quality audio at an audience device and to advise other audience devices on how best to receive the transmitted audio.

[0039] Referring to Figure 1, a schematic diagram 100 illustrates an exemplary teleconferencing scenario in which the described methods and systems may be implemented. A source device 101 transmits audio to multiple audience devices 111-115. This may be via various forms of teleconferencing between the source device 101 and the audience devices 111-115, each of which may be, for example, a mobile communication device, such as a mobile phone, or a computing device, such as a desktop or laptop computer. A user's device may be both a source device 101 and an audience device 111-115, depending on whether the user is a presenter or participant who can contribute audio, or a non-contributing participant.

[0040] The source device 101 and the audience devices 111-115 may communicate with a server 130 that provides feedback functionality in the form of a feedback system 131. In an exemplary embodiment, the feedback system 131 may be provided as a web service with applications provided on the source device 101 and the audience devices 111-115 to collect information for use by the feedback system 131. This may be incorporated within an existing conferencing web service application that may be provided via the server 130 or via a separate server that communicates with the server 130 of the feedback system 131.

[0041] 1 illustrates simplified common factors that may group subsets of audience devices 111-115. One example of a common factor may be the location of audience devices 111-115, as shown by audience device 1 (111) and audience device 2 (112) being in region A (141), and audience device 3 (113), audience device 4 (114), and audience device 5 (115) being in region B (142). A region may be a geographic area, such as a particular country, a particular state, a particular province, a particular territory, or an area with definable characteristics but not necessarily fixed boundaries. Another example of a common factor may be the form of communication used with source device 101. This is represented by a subset of audience devices in the form of audience device 1 (111), audience device 3 (113) and audience device 4 (114) that use web communication 121, and a subset of audience device 2 (112) and audience device 5 (115) that use phone communication 122.

[0042] The audience device common factors are envisioned to be more complex than the simple version shown in FIG. 1, and may include a combination of one or more of the following:

[0043] (a) Location factors, which may include, for example, a country, a state, a city, an organizational campus, or a portion of a building, such as a floor or room, etc.

[0044] (b) Connection factors, which may include, for example, a connection via a cellular network, a type of cellular network, such as a type of cellular network including those via a cellular network operator provider or by a category of data network, a landline telephone connection, a type of landline telephone network, a telephone network, such as optical fiber, cable, copper wire, a type of Wi-Fi network or a Wi-Fi network provider, etc.

[0045] (c) A connectivity factor combined with a location factor, for example, a connectivity factor combined with a location factor, which may encompass a subnet of multiple devices connecting via the Internet, a portion of a telephone network, etc.

[0046] (d) Device factors, which may include, for example, the type of browser being used, the type of device, etc.

[0047] The feedback system 131 may evaluate the audio quality at the audience devices 111-115 and analyze it against common factors for the audience devices 111-115 to determine if there is a correlation that indicates that the audio quality can be attributed to one or more common factors. Issues that affect audio quality may be related to the common factors for the audience devices 111-115, and identifying groups of audience devices 111-115 that have similar audio quality can narrow down the common factors that can affect the quality.

[0048] For example, if only audience devices 111 and 112 in area A (141) have poor quality, the poor quality may be due to location. However, if only audience devices 113 and 114 connecting via web communications 121 in area B (142) have poor quality, the poor quality may be due to problems with the web communications network in that area.

[0049] 2, a flow chart 200 illustrates an exemplary implementation of the described method performed in a feedback system 131 provided in a server 130. For example, the server 130 may be a server that provides teleconferencing functionality.

[0050] The method may obtain 201 audio quality information received at each audience device and obtained from a plurality of audience devices, which may be obtained in real time as the plurality of audience devices receive transmitted audio from a remote source device over a communication channel.

[0051] The audio information can take various forms, and different embodiments are described below. In some implementations, the audio information may be processed at the audience devices 111-115 to generate audio quality information in the form of an audio quality measure or level that is sent to the feedback system 131. For example, if the audio is a speaking voice, a speech-to-text conversion process may be performed at the audience devices 111-115 on the received voice, allowing the resulting text to be analyzed to determine a quality level based on the rate of converted words. The audio quality levels received at the feedback system 131 from different audience devices 111-115 may be compared to determine groups of audience devices 111-115 that have the same quality level.

[0052] In other embodiments, the audio information may be measured parameters of characteristics of the received audio signal that may be sent to the feedback system 131. This may apply to voice or other forms of audio. The characteristic parameters may include frequency, amplitude, power, noise, etc. Audio information in the form of parameter data may be sent from the audience devices 111-115 to the feedback system 131 for processing and evaluation. The evaluation may be performed by comparison with audio information received from other audience devices 111-115, or the transmitted audio of the source device 101, or a combination thereof.

[0053] The method may obtain (202) one or more common factors for the audience devices 111-115. Information regarding the common factors for each audience device 111-115 may be obtained by a feedback system 131 from the audience devices 111-115, for example, at the start of a teleconferencing session or if any changes to the factors occur during transmission. In some implementations, the feedback system 131 at the server may be able to obtain information regarding the factors remotely from connections of the audience devices 111-115 with a remote server 130. The method may classify (203) one or more subsets of the plurality of audience devices 111-115 by one or more common factors for each subset. The classification may be performed independently of the obtained audio quality information or may be performed as part of the analysis described below.

[0054] The method may analyze audio quality according to information received from multiple audience devices 111-115 in the same conference session along with common factors for the multiple audience devices 111-115 to determine 204 one or more common factors that affect the received audio quality. This may be done by correlating the common factors with the received measured audio quality. This may use a previously determined classification or may result in a classification as part of the analysis.

[0055] Various forms of correlation and threshold audio quality parameters may be applied. As a simple example, if the measured audio quality for each of a subset of audience devices sorted by a common factor is all below a threshold measurement, the common factor may be the cause of the low quality. In a more complex analysis, a first subset having one or more common factors may be determined to be experiencing low audio quality, while a second subset having one or more other common factors may be determined to be experiencing high quality audio, suggesting that members of the first subset should modify all factors that can be modified to contribute to the common factor of the second subset.

[0056] The method provides (205) feedback related to information about one or more common factors determined to be responsible for poor quality, and optionally good quality. This may be provided to audience devices 111-115 that are members of a subset of one or more common factors determined to be responsible for audio quality. The feedback may also be provided to the source device 101. If the cause is under the control of the user, such as if an audience user changes to another communication channel or a source user moves closer to a microphone during a conference without interruption, the feedback may be provided as a notification on the screen of the audience device 111-115 or the source device 101 to avoid an audio interruption. The feedback may enable the user of the audience device 111-115 or the source device to take appropriate action. The feedback may also include information about one or more common factors determined to result in good quality, so that the information about the one or more common factors determined to result in good quality can be used by the audience user to change their factors, such as the network being used.

[0057] For example, if audience devices using the same communication means connecting to a teleconference have similar quality that is worse than audience devices connected via a different means, this group of audience users will recognize this and change to a different connection means.

[0058] In cases where the quality of all audience devices has similar bad quality, this can be fed back to the source device so that the speaker can take corrective action by moving closer to the microphone or by making other adjustments on the source device, such as removing background noise.

[0059] The described method provides an end-to-end path between the speaker and the audience. This allows the speaker and the audience to be aware of how their audio signal is being received and to take appropriate action to minimize interruptions to the conference. By using the described method, the speaker can be aware of how well their audio signal is being received at the audience's end. This can allow the speaker to adjust the audio signal to make it clearer and better. The audience can be aware if the problem is with the connection / area, and can therefore change to a different connection method. This method can significantly improve the flow of the conference.

[0060] The identity of source device 101 may change during the course of a conference session as different participants speak, and the method may adapt to such changes in real time to evaluate the audio received at the new combination of audience devices 111-115.

[0061] The method may operate to provide feedback with a small delay from real time caused by processing the audio signal and determining the common factor. The assessment of audio quality may be performed continuously or periodically on samples of the received audio.

[0062] Referring to FIG. 3A, a flow chart 300 illustrates an exemplary implementation of the described method.

[0063] When a teleconference session begins, the presenter transmits (311) an audio signal from source device 101. Feedback system 131 runs on teleconference server 130 and detects (331) when a person in the teleconference is speaking. Feedback system 131 queries server 130 and obtains information identifying source device 101 as the endpoint with which the speaker is connected to the teleconference session and identifies those audio signals being received. The identity of source device 101 may change during the course of the session as different participants speak, and feedback system 131 may adapt to such changes in real time.

[0064] Components of the feedback system 131 executing on each of the audience devices 111-115 detect (321) the audio signal received from the source device 101 and convert (322) the audio signal to plain text using speech-to-text conversion software or a similar application programming interface (API) service. There are many existing speech-to-text conversion software products that can do this, such as the IBM Watson™ Speech to Text API. The speech-to-text conversion process can be performed continuously or periodically on a sample portion of the received audio.

[0065] A component of the feedback system 131 executing on the audience devices 111-115 determines (323) the received audio quality from the derived text, which may be measured by the ratio of converted words to unconverted words, and provides a quality level based on that ratio. This provides a quick quality assessment and does not require other information.

[0066] If the obtained text is good enough, i.e., whenever the speaker speaks, the audio can be successfully converted to text, and the audio signal is considered to be of good quality. For example, the speaker said, "This is the summary of the session," and the converted text was, "This is the summary of the session." For each spoken word, there is a corresponding converted text word. The conversion rate is 100%, indicating good quality.

[0067] If the converted text is found to be fragmented over the duration of the audio signal, i.e., if there are gaps in the text or in the sample period of the audio signal, the audio is considered to be of poor quality, even if the speaker spoke in those gaps. For example, the speaker said, "This is the summary of the session" during a certain period, e.g., the past two seconds. The converted text was "This _ the _ _ the session." Each "_" indicates that there is an audio signal at that time, but the signal cannot be converted to text. In the example shown (English), the rate is 4 out of 7 words successfully converted to text. This is considered to be of poor quality. Quality assessment can be performed on chunks of several words, e.g., 5 words. The level of the rate considered good or bad can be adjusted by an operator at the teleconference server or by a user at the audience device.

[0068] As an alternative method (323) of determining audio quality at the audience devices 111-115, a component of the feedback system 131 executing on the source device 101 may convert (312) the audio signal at the source device 111-115 and send (313) the converted text to the audience devices 111-115 along with the transmitted (311) audio signal. A component at the audience device 111-115 may compare the converted (322) text obtained from the received audio signal (321) at the audience device 111-115 with the received converted text converted (312) at the source device 101. The text comparison may be used to determine the quality level of the received audio signal at the audience device 111-115. This may result in a slight delay while waiting for the source device 101 to send the converted text. It may be the case that only samples of the converted text are sent for comparison at regular intervals for a few spoken words.

[0069] The feedback system 131 components at the audience devices send (324) the quality levels of the received audio signals to the feedback system 131 at the teleconference server 130. The feedback system 131 components at the audience devices send (325) their common factors, such as their connection area and connection means, to the feedback system 131 at the teleconference server 130. Information about the common factors (325) of the audience devices 111-115 can be sent along with the quality level information or can be collected by the feedback system 131 at registration or at the start of a session and updated if the common factors change.

[0070] The feedback system 131 may receive (332) audio quality information from the audience devices 111-115 of the session. The feedback system 131 may also receive common factor information from the audience devices 111-115 of the session. These types of information may be received together from the audience devices 111-115 periodically during the session or may be received separately at different times.

[0071] The feedback system 131 may classify the audience devices 111-115 in the session by their common factors and analyze the common factors with respect to the audio quality information to determine (334) the common factors that affect the audio quality received at the audience devices 111-115.

[0072] The feedback system 131 provides (335) feedback regarding common factors that affect audio quality to the source device (314) or to the audience device (326), or a combination thereof.

[0073] For example, if the audio quality for one group of area and connection combinations is worse than that of another group, a message or signal may be sent to the audience devices in that group indicating on the device's user interface the audio quality and suggesting connecting via a different connection method.

[0074] If the quality across all groups is poor, the speaker at the source device may be notified that the audio quality transmitted from their device is poor. The notification may be in the form of a graphic indicator symbol or light, such as a green indicator for high quality and a red indicator for poor quality. The speaker can view the indicator and adjust their speaking into the microphone accordingly.

[0075] Referring to FIG. 3B, a flow chart 350 illustrates another exemplary embodiment of the described method.

[0076] 3A in that when a teleconference session begins, a presenter transmits (351) an audio signal from source device 101. Feedback system 131 executes on teleconference server 130 and detects (371) when a person is speaking in the teleconference. Feedback system 131 queries server 130 to obtain information identifying source device 101 as the endpoint at which the speaker is connected to the teleconference session and identifies the speaker's received audio signal. The identification of source device 101 may change during the course of a session at which different participants speak, and feedback system 131 may adapt to such changes in real time.

[0077] Components of the feedback system 131 running on each of the audience devices 111-115 detect (361) the audio signal received from the source device 101 and, unlike the method of FIG. 3A, send (362) audio information to the feedback system 131 in the form of raw audio signal data or specific parameters of the audio signal data.

[0078] The feedback system 131 components at the audience devices also send (363) their common factors, such as their connection area and connection means, to the feedback system 131 at the teleconference server 130. Information about the common factors (363) of the audience devices 111-115 can be sent along with the audio information (362) or can be collected by the feedback system 131 at registration or at the start of a session and updated if the factors change.

[0079] The feedback system 131 may receive (372) audio quality information from the audience devices 111-115 during the session. The feedback system 131 may process and compare (373) the audio information received from the audience devices 111-115 during the session and determine audience devices 111-115 that have similar audio information, which may indicate a low or high quality level.

[0080] The audio information may be audio characteristic parameters, such as measurements of frequency and amplitude variations of the audio received at the audience devices 111-115. The audio information (372) received by the feedback system 131 may be compared to audio signals from the source device, or audio information received from other audience devices 111-115, or a combination thereof.

[0081] The feedback system 131 may also receive common factor information from the audience devices 111-115 in the session, and the feedback system 131 may classify the audience devices 111-115 in the session by their common factors (374). The feedback system 131 may analyze the common factors for the audio information to determine (375) common factors that affect the audio quality received at the audience devices 111-115.

[0082] The feedback system 131 provides (376) feedback regarding common factors that affect audio quality to the source device (352) or to the audience device (364), or a combination thereof.

[0083] Referring to FIG. 4, a block diagram shows a system 400 comprising a server 130 providing a feedback system 131 and a computing device 410 providing the functionality of an audience device and a source device used by an audience user or source providing user during a transmission session and including a feedback system component 440 for interacting with the feedback system 131 of the server 130.

[0084] Server 130 may include at least one processor 401, circuitry for performing the functions of the described components, which may be hardware modules or software units running on at least one processor. Multiple processors executing parallel processing threads may be provided, allowing parallel processing of some or all of the component's functions. Memory 402 may be configured to provide computer instructions 403 to at least one processor 401 to perform the component's functions.

[0085] The feedback system 131 provided by the server 130 may include an audio information acquisition component 431 for acquiring audio information of audio signals received at and acquired from audience devices in a transmission session. In one embodiment, the audio information acquisition component 431 may acquire audio signal parameter data from multiple audience devices, and the feedback system 131 may include an audio comparison component 435 for comparing audio signal parameters of the multiple audience devices to determine a subset of the multiple audience devices having similar received audio signals.

[0086] The feedback system 131 may include a factor acquisition component 405 for acquiring factor details for each computing device 410 and a classification component 432 for classifying one or more subsets of audience devices by one or more common factors per subset. The classification component 432 may group a subset of multiple audience devices by one or more common factors.

[0087] Feedback system 131 may comprise an analysis component 433 for using a classification of a subset of a plurality of audience devices to analyze the obtained audio information from the plurality of audience devices to determine one or more common factors that affect the received audio quality at the identified subset of a plurality of audience devices classified by the one or more common factors. Analysis component 433 may comprise a correlation component 438 for determining a correlation between the one or more common factors and the audio quality level of the identified subset.

[0088] The feedback system 131 may include a feedback component 434 for providing feedback of one or more common factors to at least one (or all) of the audience devices in the identified subset, to the source device, or to both the audience devices and the source device in the identified subset. The feedback component 434 may dynamically provide feedback of the one or more common factors during the live transmission.

[0089] Feedback system 131 may further comprise an overall quality component 436 for analyzing the acquired audio information from multiple audience devices to determine if the audio information is below a threshold quality for all audience devices. Feedback component 434 may provide feedback to the source device that the received overall audio quality is below a required quality.

[0090] The feedback system 131 may comprise a device detection component 437 for detecting source devices of transmitted audio signals in a transmission session and for determining from which audience devices to obtain audio information in the transmission session.

[0091] The feedback system 131 may comprise a configuration component 439 for receiving a configuration of the audio quality level.

[0092] Multiple computing devices 410 may be provided with a feedback system component 440 for interacting with the feedback system 131, and each computing device 410 may function as a source device, an audience device, or a combination thereof during a transmission session. The feedback system component 440 may be provided as a web service or a downloadable application on the computing device 410.

[0093] Each computing device 410 may include at least one processor 411, circuitry for performing the functions of the described components, which may be a hardware module or a software unit running on the at least one processor 411. Memory 412 may be configured to provide computer instructions 413 to the at least one processor 411 to perform the functions of the components.

[0094] The feedback system component 440 may include an audio information providing component 444 for providing audio information to the audio information obtaining component 431 in the feedback system 131 of the server. The feedback system component 440 may include a factor providing component 447 for providing factor information to the factor obtaining component 405 in the feedback system 131 of the server.

[0095] In one embodiment, the feedback system component 440 includes an audio quality level component 441 for obtaining an audio quality level determined at one audience device by processing a received audio signal. The feedback system component 440 may also include an audio signal processing component 442 for processing the received audio signal to assess the audio quality level, and a speech-to-text conversion component 443 for converting the audio signal using a speech-to-text conversion process and analyzing the resulting text to assess the audio quality level. The speech-to-text conversion component 443 may use a remote speech-to-text conversion service 450. The audio information provision component 444 may provide the audio quality level determined at the computing device 410.

[0096] In other embodiments, the feedback system component 440 may comprise an audio parameter collection component 445 for collecting received audio parameter data and sending it to the feedback system 131 for processing by an audio information provision component 444.

[0097] The feedback system component 440 at the computing device 410 may include a feedback receiving component 446 for receiving feedback of common parameters that affect the received audio quality at the computing device 410 functioning as an audience device or as a source device.

[0098] Figure 5 illustrates a block diagram of components of a computing system that may be implemented as server 130 or as a user computing device used as audience devices 111-115 or source device 101, according to one embodiment of the invention. It should be understood that Figure 5 provides only an example of one implementation and is not meant to imply any limitation with regard to the environment in which various embodiments may be implemented. Many modifications to the depicted environment may be made.

[0099] A computing system may include one or more processors 502, one or more computer-readable RAMs 504, one or more computer-readable ROMs 506, one or more computer-readable storage media 508, device drivers 512, read / write drives or interfaces 514, and network adapters or interfaces 516, all interconnected through a communications fabric. The communications fabric 518 may be implemented with any architecture designed to pass data or control information, or a combination thereof, between processors (e.g., microprocessors, communications and network processors, etc.), system memory, peripheral devices, and other hardware components in the system.

[0100] One or more operating systems 510 and application programs 511, such as feedback system 131 and feedback system component 440, are stored on one or more computer-readable storage media 508 for execution by one or more processors via one or more of the respective RAMs 504 (which typically include cache memory). In the illustrated embodiment, each of the computer-readable storage media 508 can be an internal hard drive magnetic disk storage device, a CD-ROM, a DVD, a memory stick, magnetic tape, a magnetic disk, an optical disk, a semiconductor storage device such as RAM, ROM, EPROM, flash memory, or any other computer-readable storage medium capable of storing computer programs and digital information in accordance with embodiments of the present invention.

[0101] The computing system may also include a R / W drive or interface 514 for reading from and writing to one or more portable computer-readable storage media 526. Application programs 511 on the computing system may be stored on one or more portable computer-readable storage media 526 and may be read via the respective R / W drive or interface 514 and loaded onto the respective computer-readable storage media 508.

[0102] The computing system may also include a network adapter or interface 516, such as a TCP / IP adapter card or a wireless communication adapter. An application program 511 on the computing system may be downloaded to the computing device from an external computer or external storage device via a network (e.g., the Internet, a local area network, or other wide area network or a wireless network) and the network adapter or interface 516. From the network adapter or interface 516, the program may be loaded into the computer-readable recording medium 508. The network may include copper wire, optical fiber, wireless transmissions, routers, firewalls, switches, gateway computers, and edge servers.

[0103] The computing system may also include a display screen 520, a keyboard or keypad 522, and a computer mouse or touchpad 524. The device driver 512 interfaces to the display screen 520 for imaging, to the keyboard or keypad 522, to the computer mouse or touchpad 524, or to the display screen 520 for pressure sensing of alphanumeric input and user selection, or a combination thereof. The device driver 512, the R / W drive or interface 514, and the network adapter or interface 516 may include hardware and software stored on the computer readable storage medium 508 or the ROM 506, or a combination thereof.

[0104] The present invention may be a system, method, or computer program product, or any combination thereof, at any level of technical detail that may be integrated. The computer program product may include one or more computer-readable storage media having computer-readable program instructions for causing a processor to perform aspects of the present invention.

[0105] The computer-readable storage medium may be a tangible device capable of holding and storing instructions for use by an instruction execution device. The computer-readable storage medium may be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. A non-exhaustive list of more specific examples of computer-readable storage media includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as a punch card or a ridge structure in a groove in which instructions are recorded, or any suitable combination thereof. As used herein, a computer-readable storage medium should not be construed as a transitory signal per se, such as an electric wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse passing through a fiber optic cable), or an electrical signal transmitted over an electrical wire.

[0106] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to an individual computing device / processing device or to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, or a wireless network, or a combination thereof. The network may be comprised of copper transmission cables, fiber optic transmission cables, wireless transmissions, routers, firewalls, switches, gateway computers, or edge servers, or a combination thereof. A network adapter card or network interface in each computing device / processing device receives the computer-readable program instructions from the network and transmits the computer-readable program instructions to the individual computing device / processing device for storage in a computer-readable storage medium.

[0107] Computer-readable program instructions for carrying out operations of the present invention may be either assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state-setting data, configuration data for an integrated circuit, or source or object code written in any combination of one or more programming languages, such as object-oriented programming languages, object-oriented programming languages (e.g., Smalltalk, C++, etc.), and procedural programming languages (e.g., the "C" programming language or similar programming languages). The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, partially on the user's computer as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer via any type of network, such as a local area network (LAN) or a wide area network (WAN), or the connection may be to an external computer (e.g., over the Internet using an Internet Service Provider). In some embodiments, electronic circuits, such as programmable logic circuits, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), may execute computer-readable program instructions by utilizing state information of the computer-readable program instructions to personalize the electronic circuitry to perform aspects of the invention.

[0108] Aspects of the present invention are described herein with reference to flowchart illustrations or block diagrams, or combinations thereof, of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations or block diagrams, or combinations thereof, and combinations of blocks in the flowchart illustrations or block diagrams, or combinations thereof, can be implemented by computer-readable program instructions.

[0109] These computer-readable program instructions may be provided to a processor of a computer or other programmable data processing apparatus, such that the instructions, executing on the processor of the computer or other programmable data processing apparatus, generate means for implementing the functions / acts identified in one or more blocks of the flowcharts or block diagrams, or combinations thereof, to produce a machine. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer-programmable data processing apparatus or other device, or combinations thereof, to function in a particular manner, such that the computer-readable storage medium having stored thereon instructions includes an article of manufacture containing instructions that implement aspects of the functions / acts identified in one or more blocks of the flowcharts or block diagrams, or combinations thereof.

[0110] The computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device such that the instructions, which execute on the computer, other programmable data processing apparatus, or other device, implement the functions / acts identified in one or more blocks of the flowcharts or block diagrams, or combinations thereof, causing the computer, other programmable apparatus, or other device to perform a series of operational steps to generate a computer-implemented process.

[0111] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowcharts or block diagrams may represent a module, segment, or portion of instructions, which includes one or more executable instructions for implementing one or more specified logical functions. In some alternative implementations, the functions shown in the blocks may occur out of the order shown in the figures. For example, two blocks shown in succession may actually be accomplished as a single step performed simultaneously, substantially simultaneously, partially, or fully in a time-overlapping manner, depending on the functionality involved, or the blocks may be performed in the reverse order. It should be noted that each block of the block diagrams or flowchart diagrams or combinations thereof, and combinations of multiple blocks in the block diagrams or flowchart diagrams or combinations thereof, may be implemented by a special-purpose hardware-based system that performs the specified functions or operations, or may execute a combination of special-purpose hardware and computer instructions.

[0112] Cloud Computing

[0113] Although this disclosure includes detailed descriptions related to cloud computing, it should be understood that implementation of the teachings recited herein is not limited to cloud computing environments. Rather, embodiments of the present invention can be implemented in conjunction with any other type of computing environment now known or later developed.

[0114] Cloud computing is a service delivery model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal administrative effort or interaction with the service provider. The cloud model can include at least five characteristics, at least three service models, and at least four deployment models.

[0115] The features are as follows:

[0116] On-demand self-service: Cloud consumers can unilaterally provision computing capacity, such as server time and network storage, as needed without the need for human interaction with the provider of the service.

[0117] Broad network access: Functionality is available over the network and accessed via standard mechanisms that facilitate use by heterogeneous thin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

[0118] Resource Pooling: A provider's computing resources are pooled to serve multiple consumers using a multi-tenant model, and various physical and virtual resources are dynamically allocated and reallocated according to demand. Consumers generally have no control or knowledge of the exact location of the provided resources, but are said to be location-independent in that they may be able to identify a location at a higher level of abstraction (e.g., country, state, or data center).

[0119] Rapid Elasticity: Capabilities can be quickly and elastically provisioned, sometimes automatically, quickly scaled out, quickly released and quickly scaled in. To the consumer, the capabilities available for provisioning are often unlimited and can be purchased in any quantity at any time.

[0120] Service Metering: Cloud systems automatically control and optimize resource usage by using metering capabilities at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active user accounts). Resource usage can be monitored, controlled, and reported, providing transparency to both providers and consumers of the services being used.

[0121] The service model is as follows:

[0122] Software as a Service (SaaS): The ability to offer consumers the ability to use a provider's applications running on a cloud infrastructure. The applications are accessible from a variety of client devices through a thin-client interface, such as a web browser (e.g., web-based email). The consumer does not manage or control the underlying cloud infrastructure, including the network, servers, operating systems, storage, or even individual application functions, with the possible exception of limited user-specific application configuration settings.

[0123] Platform as a Service (PaaS): The capability offered to a consumer to deploy consumer-created or acquired applications, created using programming languages and tools supported by the provider, onto a cloud infrastructure. The consumer does not manage or control the underlying cloud infrastructure, including networks, servers, operating systems, or storage, but does have control over the deployed applications and, in some cases, the application hosting environment configuration.

[0124] Infrastructure as a Service (IaaS): The capability offered to consumers to provision processing, storage, network, and other basic computing resources on which they can deploy and run any software, which may include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure, but does have control over the operating system, storage, deployed applications, and in some cases, limited control over the selection of network components (e.g., host firewalls).

[0125] The deployment models are as follows:

[0126] Private Cloud: Cloud infrastructure is operated exclusively for an organization. The cloud infrastructure may be managed by the organization or a third party and may reside on-premises or off-premises.

[0127] Community Cloud: Cloud infrastructure is shared by several organizations and supports a specific community with common concerns (e.g., mission, security requirements, policies, and compliance considerations). The cloud infrastructure may be managed by the organizations or a third party and may reside on-premises or off-premises.

[0128] Public Cloud: Cloud infrastructure is available to the general public or large industry groups and is owned by organizations that sell cloud services.

[0129] Hybrid Cloud: A cloud infrastructure is a blend of two or more clouds (private, community, or public) that remain unique entities but are brought together by standardized or proprietary technologies that enable data and application portability (e.g., cloud bursting for load balancing between clouds).

[0130] A cloud computing environment is service oriented with a focus on statelessness, low coupling, modularity, and semantic interoperability. At the heart of cloud computing is an infrastructure comprising a network of interconnected nodes.

[0131] Referring now to FIG. 6 , an exemplary cloud computing environment 50 is illustrated. As shown, the cloud computing environment 50 includes one or more cloud computing nodes 10, with which local computing devices used by cloud consumers, such as a personal digital assistant (PDA) or mobile phone 54A, a desktop computer 54B, a laptop computer 54C, or an automobile computer system 54N, or any combination thereof, may communicate. The nodes 10 may also communicate with each other. The nodes 10 may be physically or virtually grouped into one or more networks (not shown), such as a private cloud, community cloud, public cloud, or hybrid cloud, or any combination thereof, as described hereinabove. This allows the cloud computing environment 50 to provide infrastructure, platform, or software, or any combination thereof, as a service without the cloud consumer having to maintain resources on their local computing device. It will be understood that the types of computing devices 54A-N shown in FIG. 6 are intended to be illustrative only, and that the computing node 10 and cloud computing environment 50 can communicate with any type of computerized device (e.g., using a web browser) over any type of network or network-addressable connection or combination thereof.

[0132] Referring now to Figure 7, a set of functional abstraction layers provided by cloud computing environment 50 (Figure 6) is shown. It should be understood that the components, layers, and functions shown in Figure 7 are intended to be merely exemplary, and that embodiments of the present invention are not limited thereto. As shown, the following layers and corresponding functions are provided:

[0133] The hardware and software layer 60 includes hardware and software components. Examples of hardware components include mainframes 61, RISC (Reduced Instruction Set Computer) architecture-based servers 62, servers 63, blade servers 64, storage devices 65, and networks and networking components 66. In some embodiments, software components include network application server software 67 and database software 68.

[0134] The virtualization layer 70 provides an abstraction layer from which the following examples of virtual entities are provided: virtual servers 71, virtual storage 72, virtual networks 73, including, for example, virtual private networks, virtual applications and operating systems 74, and virtual clients 75.

[0135] In one example, management layer 80 may provide the following functions: Resource provisioning 81 provides dynamic procurement of computing and other resources used to execute tasks within the cloud computing environment. Metering and pricing 82 provides cost tracking as resources are utilized within the cloud computing environment and billing or invoicing for the consumption of these resources. In one example, these resources may include application software licenses. Security provides identity verification for cloud consumers and tasks and protection for data and other resources. User portal 83 provides access to the cloud computing environment for consumers and system administrators. Service level management 84 provides allocation and management of cloud computing resources so that required service levels are met. Service level agreement (SLA) planning and fulfillment 85 provides pre-provisioning and procurement of cloud computing resources where future requirements are predicted according to SLAs.

[0136] The workload tier 90 provides examples of functions for which a cloud computing environment may be utilized. Examples of workloads and functions that may be provided from this tier include mapping and navigation 91, software development and lifecycle management 92, virtual classroom instructional delivery 93, data analytics processing 94, transaction processing 95, and predictively selecting virtual reality content 96 to proactively adapt to later available bandwidth conditions.

[0137] The computer program product of the present invention includes one or more computer-readable hardware storage devices having computer-readable program code stored therein, the program code being executable by one or more processors to implement the methods of the present invention.

[0138] The computer system of the present invention comprises one or more processors, one or more memories, and one or more computer-readable hardware storage devices, the one or more hardware storage devices containing program code executable by the one or more processors via the one or more memories for implementing the methods of the present invention.

[0139] The descriptions of various embodiments of the present invention are presented for illustrative purposes but are not intended to be exhaustive or to be limited to the disclosed embodiments. Similarly, examples of features or functions of embodiments of the present disclosure described herein, whether used in describing a particular embodiment or described as an example, are not intended to limit the embodiments of the present disclosure described herein or to limit the disclosure to the examples described herein. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terms used herein have been selected to explain the principles of the embodiments, practical applications or technical improvements to commercially available technology, or to enable those skilled in the art to understand the embodiments disclosed herein.

[0140] Improvements and modifications can be made to what has been described above without departing from the scope of the present invention.

Claims

1. 1. A computer-implemented method for audio quality feedback during a live transmission from a source device received at a plurality of audience devices, the method being executed on a server and comprising: obtaining audio information of audio signals received by at least some of the audience devices in a transmission session, the obtaining including obtaining an audio quality level determined at one audience device by processing the received audio signals; classifying one or more subsets of the plurality of audience devices by one or more common factors per subset; analyzing the obtained audio information from the plurality of audience devices using a classification of the one or more subsets of the plurality of audience devices to determine one or more common factors that affect received audio quality at the identified subset of the plurality of audience devices classified by the one or more common factors; and providing feedback of the one or more common factors to at least one of a plurality of audience devices in the identified subset or to the source device, the feedback including information regarding the determined common factors affecting the audio quality. The method comprising:

2. 1. A computer-implemented method for audio quality feedback during a live transmission from a source device received at a plurality of audience devices, the method being executed on a server and comprising: obtaining audio information of audio signals received by at least some of the audience devices of the plurality of audience devices in a transmission session; classifying one or more subsets of the plurality of audience devices by one or more common factors per subset; analyzing the obtained audio information from the plurality of audience devices using a classification of the one or more subsets of the plurality of audience devices to determine one or more common factors that affect received audio quality at the identified subset of the plurality of audience devices classified by the one or more common factors; and providing feedback of the one or more common factors to at least one of a plurality of audience devices in the identified subset or to the source device. Including, obtaining audio information of audio signals received by at least some of the audience devices of the plurality of audience devices in a transmission session; obtaining audio signal parameter data from the plurality of audience devices and comparing audio signal parameters of the plurality of audience devices to determine a subset of the plurality of audience devices having similar received audio signals; Including, The method.

3. obtaining audio information of audio signals received by at least some of the audience devices of the plurality of audience devices in a transmission session; obtaining a determined audio quality level at one audience device by processing the received audio signal; The method of claim 2.

4. 4. The method of claim 3, wherein processing the received audio signal includes converting the audio signal using a speech-to-text conversion process and analyzing the resulting text to assess an audio quality level.

5. The method of claim 4 , wherein analyzing the resulting text to assess an audio quality level comprises determining a ratio of converted words to gaps in sample periods of the audio signal.

6. classifying one or more subsets of the plurality of audience devices by one or more common factors per subset; Obtaining factor details for each audience device and grouping a subset of the audience devices by one or more of the same factors. The method according to any one of claims 1 to 5, comprising:

7. analyzing the obtained audio information from the plurality of audience devices to determine if the audio information is below a threshold quality for all audience devices; and providing feedback to the source device that the overall audio quality received is below a required quality; The method of any one of claims 1 to 6, further comprising:

8. 8. The method of claim 1, further comprising detecting a source device of a transmitted audio signal in the transmission session and determining from which audience device to obtain audio information in the transmission session.

9. 9. The method of claim 1, wherein analyzing the acquired audio information from the plurality of audience devices using a classification of the one or more subsets of the plurality of audience devices comprises determining a correlation between one or more common factors and audio quality levels of the identified subsets.

10. The method of claim 9 , wherein the audio quality level is one of a configured range of audio quality levels ranging from a low quality level to a high quality level.

11. 11. The method of claim 1, wherein classifying the plurality of audience devices by a common factor includes classifying by one or more of the following groups: location, communication channel, transmission medium, and audience device configuration or type.

12. 1. A computer-implemented method for audio quality feedback during a live transmission from a source device received at a plurality of audience devices, the method being executed on a server and comprising: obtaining audio information of audio signals received by at least some of the audience devices in a transmission session, the obtaining including obtaining an audio quality level determined at one audience device by processing the received audio signals; obtaining factors associated with at least some of the audience devices in the transmission session; analyzing the audio information and the factors to determine a correlation between quality of the received audio signal and one or more common factors for the subset of the plurality of audience devices; and providing feedback of the one or more common factors to at least one of a plurality of audience devices in the subset or to the source device, the feedback including information regarding the determined common factors affecting the audio quality. The method comprising:

13. 1. A computer-implemented method for audio quality feedback during a live transmission from a source device received at a plurality of audience devices, the method being executed on a server and comprising: obtaining audio information of audio signals received by at least some of the audience devices of the plurality of audience devices in a transmission session; obtaining factors associated with at least some of the audience devices in the transmission session; analyzing the audio information and the factors to determine a correlation between quality of the received audio signal and one or more common factors for the subset of the plurality of audience devices; and providing feedback of the one or more common factors to at least one of a plurality of audience devices in the subset or to the source device. Including, analyzing the audio information and the factors includes analyzing audio information in the form of quality levels and comparing quality levels within and among groups of audience devices having one or more common factors to determine a subset of the audience devices having a shared quality level. The method.

14. 1. A system for audio quality feedback during a live transmission from a source device received at a plurality of audience devices, the system comprising: a server having a processor and a memory configured to provide computer program instructions to the processor to perform functions of the feedback system, the feedback system comprising: an audio information obtaining component for obtaining audio information of audio signals received by at least some of the audience devices in a transmission session, the obtaining of the audio information comprising obtaining an audio quality level determined at one audience device by processing the received audio signals; and a classification component for classifying one or more subsets of the plurality of audience devices by one or more common factors per subset; an analysis component for analyzing the acquired audio information from the plurality of audience devices using a classification of the one or more subsets of the plurality of audience devices to determine one or more common factors that affect received audio quality at the identified subset of the plurality of audience devices classified by the one or more common factors; a feedback component for providing feedback of the one or more common factors to at least one of a plurality of audience devices in the identified subset or to the source device, the feedback including information about the determined common factors affecting the audio quality; and Equipped with The system.

15. 1. A system for audio quality feedback during a live transmission from a source device received at a plurality of audience devices, the system comprising: a server having a processor and a memory configured to provide computer program instructions to the processor to perform functions of the feedback system, the feedback system comprising: an audio information acquisition component for acquiring audio information of audio signals received by at least some of the plurality of audience devices in a transmission session; a classification component for classifying one or more subsets of the plurality of audience devices by one or more common factors per subset; an analysis component for analyzing the acquired audio information from the plurality of audience devices using a classification of the one or more subsets of the plurality of audience devices to determine one or more common factors that affect received audio quality at the identified subset of the plurality of audience devices classified by the one or more common factors; a feedback component for providing feedback of the one or more common factors to at least one of a plurality of audience devices in the identified subset or to the source device; It is equipped with the audio information acquisition component acquires audio signal parameter data from the plurality of audience devices, and the system includes an audio comparison component that compares audio signal parameters of the plurality of audience devices to determine a subset of the plurality of audience devices having similar received audio signals. The system.

16. 16. The system of claim 14 or 15, wherein the system comprises a feedback system component provided in an audience device, the feedback system component comprising an audio quality level component for obtaining an audio quality level determined at one audience device by processing the received audio signal.

17. 17. The system of claim 16, wherein the audio quality level component comprises a processing component for processing the received audio signal, the processing component comprising a speech-to-text component for converting the audio signal using a speech-to-text process and analyzing the resulting text to assess an audio quality level.

18. 18. The system of claim 14, wherein the classification component obtains factor details for each audience device and groups a subset of multiple audience devices with one or more of the same factors.

19. 19. The system of claim 14, further comprising an overall quality component for analyzing the acquired audio information from the plurality of audience devices to determine whether the audio information is below a threshold quality for all audience devices, and wherein the feedback component provides feedback to the source device that the received overall audio quality is below a required quality.

20. The system of any one of claims 14 to 19, wherein the feedback component dynamically provides feedback of one or more common factors during the live transmission.

21. 21. The system of claim 14, further comprising a device detection component for detecting a source device of a transmitted audio signal in the transmission session and for determining from which audience device to obtain audio information in the transmission session.

22. 22. The system of claim 14, wherein the analysis component for analyzing the acquired audio information from the plurality of audience devices using a classification of the one or more subsets of the plurality of audience devices comprises a correlation component for determining a correlation between one or more common factors and audio quality levels of the identified subsets.

23. 23. The system of claim 22, further comprising a configuration component for receiving a configuration of an audio quality level.

24. 1. A system for audio quality feedback during a live transmission from a source device received at a plurality of audience devices, the system comprising: a server having a processor and a memory configured to provide computer program instructions to the processor to perform functions of the feedback system, the feedback system comprising: an audio information acquisition component for acquiring audio information of audio signals received by at least some of the plurality of audience devices in a transmission session; a factor acquisition component for acquiring factors associated with at least some of the audience devices in the transmission session; an analysis component for analyzing audio information and the factors to determine a correlation between quality of the received audio signal and one or more common factors for the subset of the plurality of audience devices; a feedback component for providing feedback of the one or more common factors to at least one of a plurality of audience devices in the subset or to the source device; It is equipped with The audio information acquisition component acquires audio signal parameter data from the plurality of audience devices, and the system includes an audio comparison component that compares audio signal parameters of the plurality of audience devices to determine a subset of the plurality of audience devices having similar received audio signals. The system.

25. 14. A computer program for audio quality feedback during a live transmission from a source device, received at a plurality of audience devices, said computer program causing a computer to perform the steps of the method of any one of claims 1 to 13.

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