This disclosure falls into the field of voice communication systems, more specifically it is related to the field of voice quality estimation in a packet based voice communication system. In particular the disclosure provides a method and device for 5 reducing a prediction error of the voice quality estimation by considering the content of lost packets. Furthermore, this disclosure provides a method and device which uses a voice quality estimating algorithm to calculate the voice quality estimate based on an input which is switchable between a first and a second input mode.

Embodiments described herein provide for the dynamic adjustment of traffic associated with audiovisual conferences or other types of communication sessions in situations where a network connection of one or more conference participants exhibits issues that may affect audio and/or video quality. The adjustment may include the determination at a particular conference participant (e.g., a particular User Equipment (“UE”)) of degraded network conditions, the generation of condensed conference information at the UE, and the outputting of the condensed conference information via the network. The condensed conference information may be included in control signaling. The condensed conference information may be used to generate reconstructed conference information, which may be distributed to other conference participants.

To obtain an appropriate evaluation value in an acoustic quality evaluation by a conversational test. An acoustic quality evaluation apparatus 3 evaluates the acoustic quality of a call performed between a near-end terminal 1 and a far-end terminal 2 via a voice communication network 4. An evaluation value presenting unit 31 displays, on a display unit 13, evaluation categories obtained by classifying each of a plurality of evaluation viewpoints into a predetermined number of levels. An input unit 14 transmits the evaluation category selected by the evaluator for each of the evaluation viewpoints, to an evaluation value determination unit 32. The evaluation value determination unit 32 determines the lowest evaluation value among evaluation values assigned to the evaluation category received from the input unit 14 as a subjective evaluation value for acoustic quality.

A conferencing system terminal device includes a display, an audio output, a user interface, a communication device, and one or more processors. The one or more processors present an audio difficulties user actuation target upon the display during an audio or video conference occurring across a network and concurrently with a presentation of conference content. Actuation of the audio difficulties user actuation target indicates that audio content associated with the audio or video conference being delivered by the audio output is impaired.

The disclosed system identifies international calling performance issues of a wireless telecommunication network. The system receives network traffic data for international calls including information about call attempts to a country. The system categorizes the country into a major category and a minor category based on the call attempts information. For a subset of countries, and for each key performance indicator in a subset of selected key performance indicators, the system monitors performance using an anomaly detection model to identify an anomaly in network performance, determines an actual value of the key performance indicator for the detected anomaly, and computes a variation value of the determined actual value based on a predicted range of values. The system ranks countries using the computed variation values, to indicate problematic parts of the wireless telecommunication network.

Techniques for performing conditional or controlled noise removal from audio that may contain background noise. The techniques involve obtaining audio from an environment that may have one or more unwanted noise sources, and converting the audio to digital audio data. The digital audio data is analyzed to detect whether there is noise in the audio. When noise is detected in the audio, noise removal is performed on the digital audio data to remove the noise from the audio. When noise is not detected in the audio, the digital audio data is further processed without performing noise removal on the digital audio data.

A wireless communication device comprising a communication unit, a storage, an operation unit, a communication quality measuring unit, and a controller that controls the communication unit and the storage, wherein the controller further controls the storage to store, when the operation unit detects a transmission starting operation during every channel frequency is used by other wireless communication devices, the voice data until the operation unit detects a transmission stopping operation;

controls the communication unit to transmit, when every channel frequency is not used and the bit error rate is smaller than a first threshold, all pieces of voice data that have not been transmitted, and to transmit, when every channel frequency is not used and the bit error rate is between the first threshold and a second threshold, a piece of divided data having a predetermined length from a head of the voice data which has not been transmitted.

Methods and systems for replaying buffered audio of a telephone call are provided herein. In some embodiments, a method for replaying buffered audio of a telephone call, comprises buffering audio data associated with a telephone call when a quality of an established data connection decreases below a first threshold quality measure; playing the buffered audio data from the buffer; determining the quality of the established data connection exceeds a second threshold quality measure; and replaying the audio data from the buffer, wherein replaying the audio comprises modifying the playback rate of the buffered audio data during playback.

Methods and systems are disclosed herein for improving the quality of audio for use in a biometric. A biometric system may use machine learning to determine whether audio or a portion of the audio should be used as a biometric for a user. A sample of the user's voice may be used to generate a voice signature of the user. Portions of the audio that do not meet a similarity threshold when compared with the voice signature may be removed from the audio. Additionally or alternatively, interfering noises may be detected and removed from the audio to improve the quality of a voice biometric generated from the audio.

There are provided mechanisms for transmitting a representation of a speech signal to a second terminal device. A method is performed by a first terminal device. The method includes obtaining a speech signal to be transmitted to the second terminal device. The method includes obtaining an indication of whether to, when encoding the speech signal into the representation, convert the speech signal to a text signal or not before transmission to the second terminal device. The indication is based on information of local ambient background noise at the first terminal device and of current network conditions between the first terminal device and the second terminal device. The method includes encoding the speech signal into the representation of the speech signal as determined by the indication. The method includes transmitting the representation of the speech signal towards the second terminal device.